Lip motion recognition of speaker based on SIFT%基于SIFT的说话人唇动识别

Institute of Scientific and Technical Information of China (English)

马新军; 吴晨晨; 仲乾元; 李园园

2017-01-01

Aiming at the problem that the lip feature dimension is too high and sensitive to the scale space,a technique based on the Scale-Invariant Feature Transform (SIFT) algorithm was proposed to carry out the speaker authentication.Firstly,a simple video frame image neat algorithm was proposed to adjust the length of the lip video to the same length,and the representative lip motion pictures were extracted.Then,a new algorithm based on key points of SIFT was proposed to extract the texture and motion features.After the integration of Principal Component Analysis (PCA) algorithm,the typical lip motion features were obtained for authentication.Finally,a simple classification algorithm was presented according to the obtained features.The experimental results show that compared to the common Local Binary Pattern (LBP) feature and the Histogram of Oriental Gradient (HOG) feature,the False Acceptance Rate (FAR) and False Rejection Rate (FRR) of the proposed feature extraction algorithm are better,which proves that the whole speaker lip motion recognition algorithm is effective and can get the ideal results.%针对唇部特征提取维度过高以及对尺度空间敏感的问题,提出了一种基于尺度不变特征变换(SIFT)算法作特征提取来进行说话人身份认证的技术.首先,提出了一种简单的视频帧图片规整算法,将不同长度的唇动视频规整到同一的长度,提取出具有代表性的唇动图片;然后,提出一种在SIFT关键点的基础上,进行纹理和运动特征的提取算法,并经过主成分分析(PCA)算法的整合,最终得到具有代表性的唇动特征进行认证;最后,根据所得到的特征,提出了一种简单的分类算法.实验结果显示,和常见的局部二元模式(LBP)特征和方向梯度直方图(HOG)特征相比较,该特征提取算法的错误接受率(FAR)和错误拒绝率(FRR)表现更佳.说明整个说话人唇动特征识别算法是有效的,能够得到较为理想的结果.

Stereo matching based on SIFT descriptor with illumination and camera invariance

Science.gov (United States)

Niu, Haitao; Zhao, Xunjie; Li, Chengjin; Peng, Xiang

2010-10-01

Stereo matching is the process of finding corresponding points in two or more images. The description of interest points is a critical aspect of point correspondence which is vital in stereo matching. SIFT descriptor has been proven to be better on the distinctiveness and robustness than other local descriptors. However, SIFT descriptor does not involve color information of feature point which provides powerfully distinguishable feature in matching tasks. Furthermore, in a real scene, image color are affected by various geometric and radiometric factors,such as gamma correction and exposure. These situations are very common in stereo images. For this reason, the color recorded by a camera is not a reliable cue, and the color consistency assumption is no longer valid between stereo images in real scenes. Hence the performance of other SIFT-based stereo matching algorithms can be severely degraded under the radiometric variations. In this paper, we present a new improved SIFT stereo matching algorithms that is invariant to various radiometric variations between left and right images. Unlike other improved SIFT stereo matching algorithms, we explicitly employ the color formation model with the parameters of lighting geometry, illuminant color and camera gamma in SIFT descriptor. Firstly, we transform the input color images to log-chromaticity color space, thus a linear relationship can be established. Then, we use a log-polar histogram to build three color invariance components for SIFT descriptor. So that our improved SIFT descriptor is invariant to lighting geometry, illuminant color and camera gamma changes between left and right images. Then we can match feature points between two images and use SIFT descriptor Euclidean distance as a geometric measure in our data sets to make it further accurate and robust. Experimental results show that our method is superior to other SIFT-based algorithms including conventional stereo matching algorithms under various

Facial expression recognition in the wild based on multimodal texture features

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Sun, Bo; Li, Liandong; Zhou, Guoyan; He, Jun

2016-11-01

Facial expression recognition in the wild is a very challenging task. We describe our work in static and continuous facial expression recognition in the wild. We evaluate the recognition results of gray deep features and color deep features, and explore the fusion of multimodal texture features. For the continuous facial expression recognition, we design two temporal-spatial dense scale-invariant feature transform (SIFT) features and combine multimodal features to recognize expression from image sequences. For the static facial expression recognition based on video frames, we extract dense SIFT and some deep convolutional neural network (CNN) features, including our proposed CNN architecture. We train linear support vector machine and partial least squares classifiers for those kinds of features on the static facial expression in the wild (SFEW) and acted facial expression in the wild (AFEW) dataset, and we propose a fusion network to combine all the extracted features at decision level. The final achievement we gained is 56.32% on the SFEW testing set and 50.67% on the AFEW validation set, which are much better than the baseline recognition rates of 35.96% and 36.08%.

Unsupervised semantic indoor scene classification for robot vision based on context of features using Gist and HSV-SIFT

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Madokoro, H.; Yamanashi, A.; Sato, K.

2013-08-01

This paper presents an unsupervised scene classification method for actualizing semantic recognition of indoor scenes. Background and foreground features are respectively extracted using Gist and color scale-invariant feature transform (SIFT) as feature representations based on context. We used hue, saturation, and value SIFT (HSV-SIFT) because of its simple algorithm with low calculation costs. Our method creates bags of features for voting visual words created from both feature descriptors to a two-dimensional histogram. Moreover, our method generates labels as candidates of categories for time-series images while maintaining stability and plasticity together. Automatic labeling of category maps can be realized using labels created using adaptive resonance theory (ART) as teaching signals for counter propagation networks (CPNs). We evaluated our method for semantic scene classification using KTH's image database for robot localization (KTH-IDOL), which is popularly used for robot localization and navigation. The mean classification accuracies of Gist, gray SIFT, one class support vector machines (OC-SVM), position-invariant robust features (PIRF), and our method are, respectively, 39.7, 58.0, 56.0, 63.6, and 79.4%. The result of our method is 15.8% higher than that of PIRF. Moreover, we applied our method for fine classification using our original mobile robot. We obtained mean classification accuracy of 83.2% for six zones.

Maturational changes in ear advantage for monaural word recognition in noise among listeners with central auditory processing disorders

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Mohsin Ahmed Shaikh

2017-02-01

Full Text Available This study aimed to investigate differences between ears in performance on a monaural word recognition in noise test among individuals across a broad range of ages assessed for (CAPD. Word recognition scores in quiet and in speech noise were collected retrospectively from the medical files of 107 individuals between the ages of 7 and 30 years who were diagnosed with (CAPD. No ear advantage was found on the word recognition in noise task in groups less than ten years. Performance in both ears was equally poor. Right ear performance improved across age groups, with scores of individuals above age 10 years falling within the normal range. In contrast, left ear performance remained essentially stable and in the impaired range across all age groups. Findings indicate poor left hemispheric dominance for speech perception in noise in children below the age of 10 years with (CAPD. However, a right ear advantage on this monaural speech in noise task was observed for individuals 10 years and older.

Fingerprint Identification Using SIFT-Based Minutia Descriptors and Improved All Descriptor-Pair Matching

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Jiuqiang Han

2013-03-01

Full Text Available The performance of conventional minutiae-based fingerprint authentication algorithms degrades significantly when dealing with low quality fingerprints with lots of cuts or scratches. A similar degradation of the minutiae-based algorithms is observed when small overlapping areas appear because of the quite narrow width of the sensors. Based on the detection of minutiae, Scale Invariant Feature Transformation (SIFT descriptors are employed to fulfill verification tasks in the above difficult scenarios. However, the original SIFT algorithm is not suitable for fingerprint because of: (1 the similar patterns of parallel ridges; and (2 high computational resource consumption. To enhance the efficiency and effectiveness of the algorithm for fingerprint verification, we propose a SIFT-based Minutia Descriptor (SMD to improve the SIFT algorithm through image processing, descriptor extraction and matcher. A two-step fast matcher, named improved All Descriptor-Pair Matching (iADM, is also proposed to implement the 1:N verifications in real-time. Fingerprint Identification using SMD and iADM (FISiA achieved a significant improvement with respect to accuracy in representative databases compared with the conventional minutiae-based method. The speed of FISiA also can meet real-time requirements.

3D-SIFT-Flow for atlas-based CT liver image segmentation.

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Xu, Yan; Xu, Chenchao; Kuang, Xiao; Wang, Hongkai; Chang, Eric I-Chao; Huang, Weimin; Fan, Yubo

2016-05-01

In this paper, the authors proposed a new 3D registration algorithm, 3D-scale invariant feature transform (SIFT)-Flow, for multiatlas-based liver segmentation in computed tomography (CT) images. In the registration work, the authors developed a new registration method that takes advantage of dense correspondence using the informative and robust SIFT feature. The authors computed the dense SIFT features for the source image and the target image and designed an objective function to obtain the correspondence between these two images. Labeling of the source image was then mapped to the target image according to the former correspondence, resulting in accurate segmentation. In the fusion work, the 2D-based nonparametric label transfer method was extended to 3D for fusing the registered 3D atlases. Compared with existing registration algorithms, 3D-SIFT-Flow has its particular advantage in matching anatomical structures (such as the liver) that observe large variation/deformation. The authors observed consistent improvement over widely adopted state-of-the-art registration methods such as ELASTIX, ANTS, and multiatlas fusion methods such as joint label fusion. Experimental results of liver segmentation on the MICCAI 2007 Grand Challenge are encouraging, e.g., Dice overlap ratio 96.27% ± 0.96% by our method compared with the previous state-of-the-art result of 94.90% ± 2.86%. Experimental results show that 3D-SIFT-Flow is robust for segmenting the liver from CT images, which has large tissue deformation and blurry boundary, and 3D label transfer is effective and efficient for improving the registration accuracy.

Scale Invariant Gabor Descriptor-Based Noncooperative Iris Recognition

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Du Yingzi

2010-01-01

Full Text Available Abstract A new noncooperative iris recognition method is proposed. In this method, the iris features are extracted using a Gabor descriptor. The feature extraction and comparison are scale, deformation, rotation, and contrast-invariant. It works with off-angle and low-resolution iris images. The Gabor wavelet is incorporated with scale-invariant feature transformation (SIFT for feature extraction to better extract the iris features. Both the phase and magnitude of the Gabor wavelet outputs were used in a novel way for local feature point description. Two feature region maps were designed to locally and globally register the feature points and each subregion in the map is locally adjusted to the dilation/contraction/deformation. We also developed a video-based non-cooperative iris recognition system by integrating video-based non-cooperative segmentation, segmentation evaluation, and score fusion units. The proposed method shows good performance for frontal and off-angle iris matching. Video-based recognition methods can improve non-cooperative iris recognition accuracy.

Scale Invariant Gabor Descriptor-based Noncooperative Iris Recognition

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Zhi Zhou

2010-01-01

Full Text Available A new noncooperative iris recognition method is proposed. In this method, the iris features are extracted using a Gabor descriptor. The feature extraction and comparison are scale, deformation, rotation, and contrast-invariant. It works with off-angle and low-resolution iris images. The Gabor wavelet is incorporated with scale-invariant feature transformation (SIFT for feature extraction to better extract the iris features. Both the phase and magnitude of the Gabor wavelet outputs were used in a novel way for local feature point description. Two feature region maps were designed to locally and globally register the feature points and each subregion in the map is locally adjusted to the dilation/contraction/deformation. We also developed a video-based non-cooperative iris recognition system by integrating video-based non-cooperative segmentation, segmentation evaluation, and score fusion units. The proposed method shows good performance for frontal and off-angle iris matching. Video-based recognition methods can improve non-cooperative iris recognition accuracy.

Contact-free palm-vein recognition based on local invariant features.

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Wenxiong Kang

Full Text Available Contact-free palm-vein recognition is one of the most challenging and promising areas in hand biometrics. In view of the existing problems in contact-free palm-vein imaging, including projection transformation, uneven illumination and difficulty in extracting exact ROIs, this paper presents a novel recognition approach for contact-free palm-vein recognition that performs feature extraction and matching on all vein textures distributed over the palm surface, including finger veins and palm veins, to minimize the loss of feature information. First, a hierarchical enhancement algorithm, which combines a DOG filter and histogram equalization, is adopted to alleviate uneven illumination and to highlight vein textures. Second, RootSIFT, a more stable local invariant feature extraction method in comparison to SIFT, is adopted to overcome the projection transformation in contact-free mode. Subsequently, a novel hierarchical mismatching removal algorithm based on neighborhood searching and LBP histograms is adopted to improve the accuracy of feature matching. Finally, we rigorously evaluated the proposed approach using two different databases and obtained 0.996% and 3.112% Equal Error Rates (EERs, respectively, which demonstrate the effectiveness of the proposed approach.

Contact-free palm-vein recognition based on local invariant features.

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Kang, Wenxiong; Liu, Yang; Wu, Qiuxia; Yue, Xishun

2014-01-01

Contact-free palm-vein recognition is one of the most challenging and promising areas in hand biometrics. In view of the existing problems in contact-free palm-vein imaging, including projection transformation, uneven illumination and difficulty in extracting exact ROIs, this paper presents a novel recognition approach for contact-free palm-vein recognition that performs feature extraction and matching on all vein textures distributed over the palm surface, including finger veins and palm veins, to minimize the loss of feature information. First, a hierarchical enhancement algorithm, which combines a DOG filter and histogram equalization, is adopted to alleviate uneven illumination and to highlight vein textures. Second, RootSIFT, a more stable local invariant feature extraction method in comparison to SIFT, is adopted to overcome the projection transformation in contact-free mode. Subsequently, a novel hierarchical mismatching removal algorithm based on neighborhood searching and LBP histograms is adopted to improve the accuracy of feature matching. Finally, we rigorously evaluated the proposed approach using two different databases and obtained 0.996% and 3.112% Equal Error Rates (EERs), respectively, which demonstrate the effectiveness of the proposed approach.

Recognition of In-Ear Microphone Speech Data Using Multi-Layer Neural Networks

National Research Council Canada - National Science Library

Bulbuller, Gokhan

2006-01-01

.... In this study, a speech recognition system is presented, specifically an isolated word recognizer which uses speech collected from the external auditory canals of the subjects via an in-ear microphone...

3D-SIFT-Flow for atlas-based CT liver image segmentation

Energy Technology Data Exchange (ETDEWEB)

Xu, Yan, E-mail: xuyan04@gmail.com [State Key Laboratory of Software Development Environment and Key Laboratory of Biomechanics and Mechanobiology of Ministry of Education, Beihang University, Beijing 100191, China and Research Institute of Beihang University in Shenzhen and Microsoft Research, Beijing 100080 (China); Xu, Chenchao, E-mail: chenchaoxu33@gmail.com; Kuang, Xiao, E-mail: kuangxiao.ace@gmail.com [School of Biological Science and Medical Engineering, Beihang University, Beijing 100191 (China); Wang, Hongkai, E-mail: wang.hongkai@gmail.com [Department of Biomedical Engineering, Dalian University of Technology, Dalian 116024 (China); Chang, Eric I-Chao, E-mail: eric.chang@microsoft.com [Microsoft Research, Beijing 100080 (China); Huang, Weimin, E-mail: wmhuang@i2r.a-star.edu.sg [Institute for Infocomm Research (I2R), Singapore 138632 (Singapore); Fan, Yubo, E-mail: yubofan@buaa.edu.cn [Key Laboratory of Biomechanics and Mechanobiology of Ministry of Education, Beihang University, Beijing 100191 (China)

2016-05-15

Purpose: In this paper, the authors proposed a new 3D registration algorithm, 3D-scale invariant feature transform (SIFT)-Flow, for multiatlas-based liver segmentation in computed tomography (CT) images. Methods: In the registration work, the authors developed a new registration method that takes advantage of dense correspondence using the informative and robust SIFT feature. The authors computed the dense SIFT features for the source image and the target image and designed an objective function to obtain the correspondence between these two images. Labeling of the source image was then mapped to the target image according to the former correspondence, resulting in accurate segmentation. In the fusion work, the 2D-based nonparametric label transfer method was extended to 3D for fusing the registered 3D atlases. Results: Compared with existing registration algorithms, 3D-SIFT-Flow has its particular advantage in matching anatomical structures (such as the liver) that observe large variation/deformation. The authors observed consistent improvement over widely adopted state-of-the-art registration methods such as ELASTIX, ANTS, and multiatlas fusion methods such as joint label fusion. Experimental results of liver segmentation on the MICCAI 2007 Grand Challenge are encouraging, e.g., Dice overlap ratio 96.27% ± 0.96% by our method compared with the previous state-of-the-art result of 94.90% ± 2.86%. Conclusions: Experimental results show that 3D-SIFT-Flow is robust for segmenting the liver from CT images, which has large tissue deformation and blurry boundary, and 3D label transfer is effective and efficient for improving the registration accuracy.

3D-SIFT-Flow for atlas-based CT liver image segmentation

International Nuclear Information System (INIS)

Xu, Yan; Xu, Chenchao; Kuang, Xiao; Wang, Hongkai; Chang, Eric I-Chao; Huang, Weimin; Fan, Yubo

2016-01-01

Purpose: In this paper, the authors proposed a new 3D registration algorithm, 3D-scale invariant feature transform (SIFT)-Flow, for multiatlas-based liver segmentation in computed tomography (CT) images. Methods: In the registration work, the authors developed a new registration method that takes advantage of dense correspondence using the informative and robust SIFT feature. The authors computed the dense SIFT features for the source image and the target image and designed an objective function to obtain the correspondence between these two images. Labeling of the source image was then mapped to the target image according to the former correspondence, resulting in accurate segmentation. In the fusion work, the 2D-based nonparametric label transfer method was extended to 3D for fusing the registered 3D atlases. Results: Compared with existing registration algorithms, 3D-SIFT-Flow has its particular advantage in matching anatomical structures (such as the liver) that observe large variation/deformation. The authors observed consistent improvement over widely adopted state-of-the-art registration methods such as ELASTIX, ANTS, and multiatlas fusion methods such as joint label fusion. Experimental results of liver segmentation on the MICCAI 2007 Grand Challenge are encouraging, e.g., Dice overlap ratio 96.27% ± 0.96% by our method compared with the previous state-of-the-art result of 94.90% ± 2.86%. Conclusions: Experimental results show that 3D-SIFT-Flow is robust for segmenting the liver from CT images, which has large tissue deformation and blurry boundary, and 3D label transfer is effective and efficient for improving the registration accuracy.

Image Mosaic Method Based on SIFT Features of Line Segment

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Jun Zhu

2014-01-01

Full Text Available This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling.

Ear biometrics in 2D and 3D localization and recognition

CERN Document Server

Prakash, Surya

2015-01-01

This book presents the state-of-the-art techniques and recent research progress on Ear Biometrics. Among the various physiological traits, the reasons for the ear to gain much attention in recent years are many folds. It has been found to be a reliable biometrics for human verification and identification. Ears are remarkably consistent and unlike face, it does not change shape with different expressions or age, and remain fixed in the middle of the side of the head against a predictable background. The book contains figures, tables and plots to illustrate the techniques in an easy and lucid manner. The book also provides an extensive literature on the subject, where readers have the benefit of receiving all the relevant material at one place in a very comprehensive manner. This book caters students, academics, researchers, practitioners who are interested in the field of Ear Biometrics and its applications in face recognition and security.

On Applicability of Tunable Filter Bank Based Feature for Ear Biometrics: A Study from Constrained to Unconstrained.

Science.gov (United States)

Chowdhury, Debbrota Paul; Bakshi, Sambit; Guo, Guodong; Sa, Pankaj Kumar

2017-11-27

In this paper, an overall framework has been presented for person verification using ear biometric which uses tunable filter bank as local feature extractor. The tunable filter bank, based on a half-band polynomial of 14th order, extracts distinct features from ear images maintaining its frequency selectivity property. To advocate the applicability of tunable filter bank on ear biometrics, recognition test has been performed on available constrained databases like AMI, WPUT, IITD and unconstrained database like UERC. Experiments have been conducted applying tunable filter based feature extractor on subparts of the ear. Empirical experiments have been conducted with four and six subdivisions of the ear image. Analyzing the experimental results, it has been found that tunable filter moderately succeeds to distinguish ear features at par with the state-of-the-art features used for ear recognition. Accuracies of 70.58%, 67.01%, 81.98%, and 57.75% have been achieved on AMI, WPUT, IITD, and UERC databases through considering Canberra Distance as underlying measure of separation. The performances indicate that tunable filter is a candidate for recognizing human from ear images.

Image feature extraction in encrypted domain with privacy-preserving SIFT.

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Hsu, Chao-Yung; Lu, Chun-Shien; Pei, Soo-Chang

2012-11-01

Privacy has received considerable attention but is still largely ignored in the multimedia community. Consider a cloud computing scenario where the server is resource-abundant, and is capable of finishing the designated tasks. It is envisioned that secure media applications with privacy preservation will be treated seriously. In view of the fact that scale-invariant feature transform (SIFT) has been widely adopted in various fields, this paper is the first to target the importance of privacy-preserving SIFT (PPSIFT) and to address the problem of secure SIFT feature extraction and representation in the encrypted domain. As all of the operations in SIFT must be moved to the encrypted domain, we propose a privacy-preserving realization of the SIFT method based on homomorphic encryption. We show through the security analysis based on the discrete logarithm problem and RSA that PPSIFT is secure against ciphertext only attack and known plaintext attack. Experimental results obtained from different case studies demonstrate that the proposed homomorphic encryption-based privacy-preserving SIFT performs comparably to the original SIFT and that our method is useful in SIFT-based privacy-preserving applications.

Gun bore flaw image matching based on improved SIFT descriptor

Science.gov (United States)

Zeng, Luan; Xiong, Wei; Zhai, You

2013-01-01

In order to increase the operation speed and matching ability of SIFT algorithm, the SIFT descriptor and matching strategy are improved. First, a method of constructing feature descriptor based on sector area is proposed. By computing the gradients histogram of location bins which are parted into 6 sector areas, a descriptor with 48 dimensions is constituted. It can reduce the dimension of feature vector and decrease the complexity of structuring descriptor. Second, it introduce a strategy that partitions the circular region into 6 identical sector areas starting from the dominate orientation. Consequently, the computational complexity is reduced due to cancellation of rotation operation for the area. The experimental results indicate that comparing with the OpenCV SIFT arithmetic, the average matching speed of the new method increase by about 55.86%. The matching veracity can be increased even under some variation of view point, illumination, rotation, scale and out of focus. The new method got satisfied results in gun bore flaw image matching. Keywords: Metrology, Flaw image matching, Gun bore, Feature descriptor

Automated Orthorectification of VHR Satellite Images by SIFT-Based RPC Refinement

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Hakan Kartal

2018-06-01

Full Text Available Raw remotely sensed images contain geometric distortions and cannot be used directly for map-based applications, accurate locational information extraction or geospatial data integration. A geometric correction process must be conducted to minimize the errors related to distortions and achieve the desired location accuracy before further analysis. A considerable number of images might be needed when working over large areas or in temporal domains in which manual geometric correction requires more labor and time. To overcome these problems, new algorithms have been developed to make the geometric correction process autonomous. The Scale Invariant Feature Transform (SIFT algorithm is an image matching algorithm used in remote sensing applications that has received attention in recent years. In this study, the effects of the incidence angle, surface topography and land cover (LC characteristics on SIFT-based automated orthorectification were investigated at three different study sites with different topographic conditions and LC characteristics using Pleiades very high resolution (VHR images acquired at different incidence angles. The results showed that the location accuracy of the orthorectified images increased with lower incidence angle images. More importantly, the topographic characteristics had no observable impacts on the location accuracy of SIFT-based automated orthorectification, and the results showed that Ground Control Points (GCPs are mainly concentrated in the “Forest” and “Semi Natural Area” LC classes. A multi-thread code was designed to reduce the automated processing time, and the results showed that the process performed 7 to 16 times faster using an automated approach. Analyses performed on various spectral modes of multispectral data showed that the arithmetic data derived from pan-sharpened multispectral images can be used in automated SIFT-based RPC orthorectification.

SIFT-CCH: Increasing the SIFT distinctness by color co-occurrence histograms

OpenAIRE

ANCUTI, Cosmin; BEKAERT, Philippe

2007-01-01

Describing regions in a distinctive way, in order to find correct correspondences in images of two separated views, represents a complex and essential task of computer vision. Until now, SIFT (Scale Invariant Feature Transform) has been proven to be the most reliable descriptor among the others. One of the main drawbacks of SIFT is its vulnerability to color images, being designed mainly for the gray images. To overcome this problem and also to increase the overall distinctness of the SIFT ...

Image-based automatic recognition of larvae

Science.gov (United States)

Sang, Ru; Yu, Guiying; Fan, Weijun; Guo, Tiantai

2010-08-01

As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (SIFT) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.

Ear Detection under Uncontrolled Conditions with Multiple Scale Faster Region-Based Convolutional Neural Networks

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Yi Zhang

2017-04-01

Full Text Available Ear detection is an important step in ear recognition approaches. Most existing ear detection techniques are based on manually designing features or shallow learning algorithms. However, researchers found that the pose variation, occlusion, and imaging conditions provide a great challenge to the traditional ear detection methods under uncontrolled conditions. This paper proposes an efficient technique involving Multiple Scale Faster Region-based Convolutional Neural Networks (Faster R-CNN to detect ears from 2D profile images in natural images automatically. Firstly, three regions of different scales are detected to infer the information about the ear location context within the image. Then an ear region filtering approach is proposed to extract the correct ear region and eliminate the false positives automatically. In an experiment with a test set of 200 web images (with variable photographic conditions, 98% of ears were accurately detected. Experiments were likewise conducted on the Collection J2 of University of Notre Dame Biometrics Database (UND-J2 and University of Beira Interior Ear dataset (UBEAR, which contain large occlusion, scale, and pose variations. Detection rates of 100% and 98.22%, respectively, demonstrate the effectiveness of the proposed approach.

SIFT applied to CBIR

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ALMEIDA, J.

2009-12-01

Full Text Available Content-Based Image Retrieval (CBIR is a challenging task. Common approaches use only low-level features. Notwithstanding, such CBIR solutions fail on capturing some local features representing the details and nuances of scenes. Many techniques in image processing and computer vision can capture these scene semantics. Among them, the Scale Invariant Features Transform~(SIFT has been widely used in a lot of applications. This approach relies on the choice of several parameters which directly impact its effectiveness when applied to retrieve images. In this paper, we discuss the results obtained in several experiments proposed to evaluate the application of the SIFT in CBIR tasks.

Traffic sign recognition based on a context-aware scale-invariant feature transform approach

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Yuan, Xue; Hao, Xiaoli; Chen, Houjin; Wei, Xueye

2013-10-01

A new context-aware scale-invariant feature transform (CASIFT) approach is proposed, which is designed for the use in traffic sign recognition (TSR) systems. The following issues remain in previous works in which SIFT is used for matching or recognition: (1) SIFT is unable to provide color information; (2) SIFT only focuses on local features while ignoring the distribution of global shapes; (3) the template with the maximum number of matching points selected as the final result is instable, especially for images with simple patterns; and (4) SIFT is liable to result in errors when different images share the same local features. In order to resolve these problems, a new CASIFT approach is proposed. The contributions of the work are as follows: (1) color angular patterns are used to provide the color distinguishing information; (2) a CASIFT which effectively combines local and global information is proposed; and (3) a method for computing the similarity between two images is proposed, which focuses on the distribution of the matching points, rather than using the traditional SIFT approach of selecting the template with maximum number of matching points as the final result. The proposed approach is particularly effective in dealing with traffic signs which have rich colors and varied global shape distribution. Experiments are performed to validate the effectiveness of the proposed approach in TSR systems, and the experimental results are satisfying even for images containing traffic signs that have been rotated, damaged, altered in color, have undergone affine transformations, or images which were photographed under different weather or illumination conditions.

A Novel Image Retrieval Based on Visual Words Integration of SIFT and SURF.

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Nouman Ali

Full Text Available With the recent evolution of technology, the number of image archives has increased exponentially. In Content-Based Image Retrieval (CBIR, high-level visual information is represented in the form of low-level features. The semantic gap between the low-level features and the high-level image concepts is an open research problem. In this paper, we present a novel visual words integration of Scale Invariant Feature Transform (SIFT and Speeded-Up Robust Features (SURF. The two local features representations are selected for image retrieval because SIFT is more robust to the change in scale and rotation, while SURF is robust to changes in illumination. The visual words integration of SIFT and SURF adds the robustness of both features to image retrieval. The qualitative and quantitative comparisons conducted on Corel-1000, Corel-1500, Corel-2000, Oliva and Torralba and Ground Truth image benchmarks demonstrate the effectiveness of the proposed visual words integration.

SIFT Meets CNN: A Decade Survey of Instance Retrieval.

Science.gov (United States)

Zheng, Liang; Yang, Yi; Tian, Qi

2018-05-01

In the early days, content-based image retrieval (CBIR) was studied with global features. Since 2003, image retrieval based on local descriptors (de facto SIFT) has been extensively studied for over a decade due to the advantage of SIFT in dealing with image transformations. Recently, image representations based on the convolutional neural network (CNN) have attracted increasing interest in the community and demonstrated impressive performance. Given this time of rapid evolution, this article provides a comprehensive survey of instance retrieval over the last decade. Two broad categories, SIFT-based and CNN-based methods, are presented. For the former, according to the codebook size, we organize the literature into using large/medium-sized/small codebooks. For the latter, we discuss three lines of methods, i.e., using pre-trained or fine-tuned CNN models, and hybrid methods. The first two perform a single-pass of an image to the network, while the last category employs a patch-based feature extraction scheme. This survey presents milestones in modern instance retrieval, reviews a broad selection of previous works in different categories, and provides insights on the connection between SIFT and CNN-based methods. After analyzing and comparing retrieval performance of different categories on several datasets, we discuss promising directions towards generic and specialized instance retrieval.

Bi-directional SIFT predicts a subset of activating mutations.

Directory of Open Access Journals (Sweden)

William Lee

Full Text Available Advancements in sequencing technologies have empowered recent efforts to identify polymorphisms and mutations on a global scale. The large number of variations and mutations found in these projects requires high-throughput tools to identify those that are most likely to have an impact on function. Numerous computational tools exist for predicting which mutations are likely to be functional, but none that specifically attempt to identify mutations that result in hyperactivation or gain-of-function. Here we present a modified version of the SIFT (Sorting Intolerant from Tolerant algorithm that utilizes protein sequence alignments with homologous sequences to identify functional mutations based on evolutionary fitness. We show that this bi-directional SIFT (B-SIFT is capable of identifying experimentally verified activating mutants from multiple datasets. B-SIFT analysis of large-scale cancer genotyping data identified potential activating mutations, some of which we have provided detailed structural evidence to support. B-SIFT could prove to be a valuable tool for efforts in protein engineering as well as in identification of functional mutations in cancer.

Image based Monument Recognition using Graph based Visual Saliency

DEFF Research Database (Denmark)

Kalliatakis, Grigorios; Triantafyllidis, Georgios

2013-01-01

This article presents an image-based application aiming at simple image classification of well-known monuments in the area of Heraklion, Crete, Greece. This classification takes place by utilizing Graph Based Visual Saliency (GBVS) and employing Scale Invariant Feature Transform (SIFT) or Speeded......, the images have been previously processed according to the Graph Based Visual Saliency model in order to keep either SIFT or SURF features corresponding to the actual monuments while the background “noise” is minimized. The application is then able to classify these images, helping the user to better...

Human action recognition using trajectory-based representation

Directory of Open Access Journals (Sweden)

Haiam A. Abdul-Azim

2015-07-01

Full Text Available Recognizing human actions in video sequences has been a challenging problem in the last few years due to its real-world applications. A lot of action representation approaches have been proposed to improve the action recognition performance. Despite the popularity of local features-based approaches together with “Bag-of-Words” model for action representation, it fails to capture adequate spatial or temporal relationships. In an attempt to overcome this problem, a trajectory-based local representation approaches have been proposed to capture the temporal information. This paper introduces an improvement of trajectory-based human action recognition approaches to capture discriminative temporal relationships. In our approach, we extract trajectories by tracking the detected spatio-temporal interest points named “cuboid features” with matching its SIFT descriptors over the consecutive frames. We, also, propose a linking and exploring method to obtain efficient trajectories for motion representation in realistic conditions. Then the volumes around the trajectories’ points are described to represent human actions based on the Bag-of-Words (BOW model. Finally, a support vector machine is used to classify human actions. The effectiveness of the proposed approach was evaluated on three popular datasets (KTH, Weizmann and UCF sports. Experimental results showed that the proposed approach yields considerable performance improvement over the state-of-the-art approaches.

Real-time billboard trademark detection and recognition in sports video

Science.gov (United States)

Bu, Jiang; Lao, Song-Yan; Bai, Liang

2013-03-01

Nowadays, different applications like automatic video indexing, keyword based video search and TV commercials can be developed by detecting and recognizing the billboard trademark. We propose a hierarchical solution for real-time billboard trademark recognition in various sports video, billboard frames are detected in the first level, fuzzy decision tree with easily-computing features are employed to accelerate the process, while in the second level, color and regional SIFT features are combined for the first time to describe the appearance of trademarks, and the shared nearest neighbor (SNN) clustering with x2 distance is utilized instead of traditional K-means clustering to construct the SIFT vocabulary, at last, Latent Semantic Analysis (LSA) based SIFT vocabulary matching is performed on the template trademark and the candidate regions in billboard frame. The preliminary experiments demonstrate the effectiveness of the hierarchical solution, and real time constraints are also met by our solution.

Multithread Face Recognition in Cloud

Directory of Open Access Journals (Sweden)

Dakshina Ranjan Kisku

2016-01-01

Full Text Available Faces are highly challenging and dynamic objects that are employed as biometrics evidence in identity verification. Recently, biometrics systems have proven to be an essential security tools, in which bulk matching of enrolled people and watch lists is performed every day. To facilitate this process, organizations with large computing facilities need to maintain these facilities. To minimize the burden of maintaining these costly facilities for enrollment and recognition, multinational companies can transfer this responsibility to third-party vendors who can maintain cloud computing infrastructures for recognition. In this paper, we showcase cloud computing-enabled face recognition, which utilizes PCA-characterized face instances and reduces the number of invariant SIFT points that are extracted from each face. To achieve high interclass and low intraclass variances, a set of six PCA-characterized face instances is computed on columns of each face image by varying the number of principal components. Extracted SIFT keypoints are fused using sum and max fusion rules. A novel cohort selection technique is applied to increase the total performance. The proposed protomodel is tested on BioID and FEI face databases, and the efficacy of the system is proven based on the obtained results. We also compare the proposed method with other well-known methods.

A SAR IMAGE REGISTRATION METHOD BASED ON SIFT ALGORITHM

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W. Lu

2017-09-01

Full Text Available In order to improve the stability and rapidity of synthetic aperture radar (SAR images matching, an effective method was presented. Firstly, the adaptive smoothing filtering was employed for image denoising in image processing based on Wallis filtering to avoid the follow-up noise is amplified. Secondly, feature points were extracted by a simplified SIFT algorithm. Finally, the exact matching of the images was achieved with these points. Compared with the existing methods, it not only maintains the richness of features, but a-lso reduces the noise of the image. The simulation results show that the proposed algorithm can achieve better matching effect.

SU-F-303-11: Implementation and Applications of Rapid, SIFT-Based Cine MR Image Binning and Region Tracking

Energy Technology Data Exchange (ETDEWEB)

Mazur, T; Wang, Y; Fischer-Valuck, B; Acharya, S; Kashani, R; Li, H; Yang, D; Zoberi, I; Thomas, M; Mutic, S; Li, H [Washington University School of Medicine, St. Louis, MO (United States)

2015-06-15

Purpose: To develop a novel and rapid, SIFT-based algorithm for assessing feature motion on cine MR images acquired during MRI-guided radiotherapy treatments. In particular, we apply SIFT descriptors toward both partitioning cine images into respiratory states and tracking regions across frames. Methods: Among a training set of images acquired during a fraction, we densely assign SIFT descriptors to pixels within the images. We cluster these descriptors across all frames in order to produce a dictionary of trackable features. Associating the best-matching descriptors at every frame among the training images to these features, we construct motion traces for the features. We use these traces to define respiratory bins for sorting images in order to facilitate robust pixel-by-pixel tracking. Instead of applying conventional methods for identifying pixel correspondences across frames we utilize a recently-developed algorithm that derives correspondences via a matching objective for SIFT descriptors. Results: We apply these methods to a collection of lung, abdominal, and breast patients. We evaluate the procedure for respiratory binning using target sites exhibiting high-amplitude motion among 20 lung and abdominal patients. In particular, we investigate whether these methods yield minimal variation between images within a bin by perturbing the resulting image distributions among bins. Moreover, we compare the motion between averaged images across respiratory states to 4DCT data for these patients. We evaluate the algorithm for obtaining pixel correspondences between frames by tracking contours among a set of breast patients. As an initial case, we track easily-identifiable edges of lumpectomy cavities that show minimal motion over treatment. Conclusions: These SIFT-based methods reliably extract motion information from cine MR images acquired during patient treatments. While we performed our analysis retrospectively, the algorithm lends itself to prospective motion

Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion

Science.gov (United States)

Deng, Ning

2014-01-01

In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, andMMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity. PMID:24683317

Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion

Directory of Open Access Journals (Sweden)

Ying Chen

2014-01-01

Full Text Available In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region’s weights and then weighted different subregions’ matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, andMMU-V1, demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity.

Efficient iris recognition based on optimal subfeature selection and weighted subregion fusion.

Science.gov (United States)

Chen, Ying; Liu, Yuanning; Zhu, Xiaodong; He, Fei; Wang, Hongye; Deng, Ning

2014-01-01

In this paper, we propose three discriminative feature selection strategies and weighted subregion matching method to improve the performance of iris recognition system. Firstly, we introduce the process of feature extraction and representation based on scale invariant feature transformation (SIFT) in detail. Secondly, three strategies are described, which are orientation probability distribution function (OPDF) based strategy to delete some redundant feature keypoints, magnitude probability distribution function (MPDF) based strategy to reduce dimensionality of feature element, and compounded strategy combined OPDF and MPDF to further select optimal subfeature. Thirdly, to make matching more effective, this paper proposes a novel matching method based on weighted sub-region matching fusion. Particle swarm optimization is utilized to accelerate achieve different sub-region's weights and then weighted different subregions' matching scores to generate the final decision. The experimental results, on three public and renowned iris databases (CASIA-V3 Interval, Lamp, and MMU-V1), demonstrate that our proposed methods outperform some of the existing methods in terms of correct recognition rate, equal error rate, and computation complexity.

Emotion Index of Cover Song Music Video Clips based on Facial Expression Recognition

DEFF Research Database (Denmark)

Kavallakis, George; Vidakis, Nikolaos; Triantafyllidis, Georgios

2017-01-01

This paper presents a scheme of creating an emotion index of cover song music video clips by recognizing and classifying facial expressions of the artist in the video. More specifically, it fuses effective and robust algorithms which are employed for expression recognition, along with the use...... of a neural network system using the features extracted by the SIFT algorithm. Also we support the need of this fusion of different expression recognition algorithms, because of the way that emotions are linked to facial expressions in music video clips....

Sifting of waste; Siktning av avfall

Energy Technology Data Exchange (ETDEWEB)

Johansson, Andreas [SP Technical Research Inst. of Sweden, Boraas (Sweden); Johnsson, Anders [Boraas Energi och Miljoe, Boraas (Sweden); Yoshiguchi, Hitomi [Stena Metall, Goeteborg (Sweden); Steenari, Britt-Marie [Chalmers Tekniska Hoegskola, Goeteborg (Sweden); Bostroem, Sara [Renova AB, Goeteborg (Sweden); Fredaeng, Julia [Dalkia, Stockholm (Sweden); Bisaillon, Mattias [Profu AB, Moelndal (Sweden); Andersson, Hans [Metso Power, Tammerfors (Finland)

2008-08-15

Waste as a fuel is characterized by high levels of inert components (ash) that may cause problems in a combustion process that result in high costs for operation and maintenance (e.g. large ash flows, high need for additives). A potential method for reduction of these costs is to separate inert components through sifting prior the combustion process. Previously it has been found that a major share of the unwanted components is found in the fine grains. However, the practical relevance of sifting has not been verified against boiler performance. Therefore, the prospects for sifting as a pre-treatment method was investigated at Boraas Energi och miljoe with the aim to characterize the composition in the fine-grained residues and to determine the effects from sifting on the boiler performance. The project includes also a short report on possible markets for the fine-grained residues. The effect target is to increase the boiler availability and to reduce the cost for operation and maintenance. The target groups for the work are owners of Energy-from-Waste plants as well as constructors of plants and sieves. The work shows that sifting can be beneficial from an economical point of view if a suitable market for the fine-grained residues is found. Several theoretical markets exist but the governing parameter is the actual costs for the post-treatment.

A street rubbish detection algorithm based on Sift and RCNN

Science.gov (United States)

Yu, XiPeng; Chen, Zhong; Zhang, Shuo; Zhang, Ting

2018-02-01

This paper presents a street rubbish detection algorithm based on image registration with Sift feature and RCNN. Firstly, obtain the rubbish region proposal on the real-time street image and set up the CNN convolution neural network trained by the rubbish samples set consists of rubbish and non-rubbish images; Secondly, for every clean street image, obtain the Sift feature and do image registration with the real-time street image to obtain the differential image, the differential image filters a lot of background information, obtain the rubbish region proposal rect where the rubbish may appear on the differential image by the selective search algorithm. Then, the CNN model is used to detect the image pixel data in each of the region proposal on the real-time street image. According to the output vector of the CNN, it is judged whether the rubbish is in the region proposal or not. If it is rubbish, the region proposal on the real-time street image is marked. This algorithm avoids the large number of false detection caused by the detection on the whole image because the CNN is used to identify the image only in the region proposal on the real-time street image that may appear rubbish. Different from the traditional object detection algorithm based on the region proposal, the region proposal is obtained on the differential image not whole real-time street image, and the number of the invalid region proposal is greatly reduced. The algorithm has the high mean average precision (mAP).

Automatic registration of remote sensing images based on SIFT and fuzzy block matching for change detection

Directory of Open Access Journals (Sweden)

Cai Guo-Rong

2011-10-01

Full Text Available This paper presents an automated image registration approach to detecting changes in multi-temporal remote sensing images. The proposed algorithm is based on the scale invariant feature transform (SIFT and has two phases. The first phase focuses on SIFT feature extraction and on estimation of image transformation. In the second phase, Structured Local Binary Haar Pattern (SLBHP combined with a fuzzy similarity measure is then used to build a new and effective block similarity measure for change detection. Experimental results obtained on multi-temporal data sets show that compared with three mainstream block matching algorithms, the proposed algorithm is more effective in dealing with scale, rotation and illumination changes.

3D ear identification based on sparse representation.

Directory of Open Access Journals (Sweden)

Lin Zhang

Full Text Available Biometrics based personal authentication is an effective way for automatically recognizing, with a high confidence, a person's identity. Recently, 3D ear shape has attracted tremendous interests in research field due to its richness of feature and ease of acquisition. However, the existing ICP (Iterative Closet Point-based 3D ear matching methods prevalent in the literature are not quite efficient to cope with the one-to-many identification case. In this paper, we aim to fill this gap by proposing a novel effective fully automatic 3D ear identification system. We at first propose an accurate and efficient template-based ear detection method. By utilizing such a method, the extracted ear regions are represented in a common canonical coordinate system determined by the ear contour template, which facilitates much the following stages of feature extraction and classification. For each extracted 3D ear, a feature vector is generated as its representation by making use of a PCA-based local feature descriptor. At the stage of classification, we resort to the sparse representation based classification approach, which actually solves an l1-minimization problem. To the best of our knowledge, this is the first work introducing the sparse representation framework into the field of 3D ear identification. Extensive experiments conducted on a benchmark dataset corroborate the effectiveness and efficiency of the proposed approach. The associated Matlab source code and the evaluation results have been made publicly online available at http://sse.tongji.edu.cn/linzhang/ear/srcear/srcear.htm.

THE IDENTIFICATION OF EAR PRINTS USING COMPLEX GABOR FILTERS

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Alexander A S Gunawan

2012-05-01

Full Text Available Biometrics is a method used to recognize humans based on one or a few characteristicsphysical or behavioral traits that are unique such as DNA, face, fingerprints, gait, iris, palm, retina,signature and sound. Although the facts that ear prints are found in 15% of crime scenes, ear printsresearch has been very limited since the success of fingerprints modality. The advantage of the useof ear prints, as forensic evidence, are it relatively unchanged due to increased age and have fewervariations than faces with expression variation and orientation. In this research, complex Gaborfilters is used to extract the ear prints feature based on texture segmentation. Principal componentanalysis (PCA is then used for dimensionality-reduction where variation in the dataset ispreserved. The classification is done in a lower dimension space defined by principal componentsbased on Euclidean distance. In experiments, it is used left and right ear prints of ten respondentsand in average, the successful recognition rate is 78%. Based on the experiment results, it isconcluded that ear prints is suitable as forensic evidence mainly when combined with otherbiometric modalities.Keywords: Biometrics; Ear prints; Complex Gabor filters; Principal component analysis;Euclidean distance

Evaluating color descriptors for object and scene recognition.

Science.gov (United States)

van de Sande, Koen E A; Gevers, Theo; Snoek, Cees G M

2010-09-01

Image category recognition is important to access visual information on the level of objects and scene types. So far, intensity-based descriptors have been widely used for feature extraction at salient points. To increase illumination invariance and discriminative power, color descriptors have been proposed. Because many different descriptors exist, a structured overview is required of color invariant descriptors in the context of image category recognition. Therefore, this paper studies the invariance properties and the distinctiveness of color descriptors (software to compute the color descriptors from this paper is available from http://www.colordescriptors.com) in a structured way. The analytical invariance properties of color descriptors are explored, using a taxonomy based on invariance properties with respect to photometric transformations, and tested experimentally using a data set with known illumination conditions. In addition, the distinctiveness of color descriptors is assessed experimentally using two benchmarks, one from the image domain and one from the video domain. From the theoretical and experimental results, it can be derived that invariance to light intensity changes and light color changes affects category recognition. The results further reveal that, for light intensity shifts, the usefulness of invariance is category-specific. Overall, when choosing a single descriptor and no prior knowledge about the data set and object and scene categories is available, the OpponentSIFT is recommended. Furthermore, a combined set of color descriptors outperforms intensity-based SIFT and improves category recognition by 8 percent on the PASCAL VOC 2007 and by 7 percent on the Mediamill Challenge.

SIFTS: Structure Integration with Function, Taxonomy and Sequences resource

Science.gov (United States)

Velankar, Sameer; Dana, José M.; Jacobsen, Julius; van Ginkel, Glen; Gane, Paul J.; Luo, Jie; Oldfield, Thomas J.; O’Donovan, Claire; Martin, Maria-Jesus; Kleywegt, Gerard J.

2013-01-01

The Structure Integration with Function, Taxonomy and Sequences resource (SIFTS; http://pdbe.org/sifts) is a close collaboration between the Protein Data Bank in Europe (PDBe) and UniProt. The two teams have developed a semi-automated process for maintaining up-to-date cross-reference information to UniProt entries, for all protein chains in the PDB entries present in the UniProt database. This process is carried out for every weekly PDB release and the information is stored in the SIFTS database. The SIFTS process includes cross-references to other biological resources such as Pfam, SCOP, CATH, GO, InterPro and the NCBI taxonomy database. The information is exported in XML format, one file for each PDB entry, and is made available by FTP. Many bioinformatics resources use SIFTS data to obtain cross-references between the PDB and other biological databases so as to provide their users with up-to-date information. PMID:23203869

Automated Photogrammetric Image Matching with Sift Algorithm and Delaunay Triangulation

DEFF Research Database (Denmark)

Karagiannis, Georgios; Antón Castro, Francesc/François; Mioc, Darka

2016-01-01

An algorithm for image matching of multi-sensor and multi-temporal satellite images is developed. The method is based on the SIFT feature detector proposed by Lowe in (Lowe, 1999). First, SIFT feature points are detected independently in two images (reference and sensed image). The features detec...... of each feature set for each image are computed. The isomorphism of the Delaunay triangulations is determined to guarantee the quality of the image matching. The algorithm is implemented in Matlab and tested on World-View 2, SPOT6 and TerraSAR-X image patches....

Visual Thing Recognition with Binary Scale-Invariant Feature Transform and Support Vector Machine Classifiers Using Color Information

OpenAIRE

Wei-Jong Yang; Wei-Hau Du; Pau-Choo Chang; Jar-Ferr Yang; Pi-Hsia Hung

2017-01-01

The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an importan...

Right-Ear Advantage for Speech-in-Noise Recognition in Patients with Nonlateralized Tinnitus and Normal Hearing Sensitivity.

Science.gov (United States)

Tai, Yihsin; Husain, Fatima T

2018-04-01

Despite having normal hearing sensitivity, patients with chronic tinnitus may experience more difficulty recognizing speech in adverse listening conditions as compared to controls. However, the association between the characteristics of tinnitus (severity and loudness) and speech recognition remains unclear. In this study, the Quick Speech-in-Noise test (QuickSIN) was conducted monaurally on 14 patients with bilateral tinnitus and 14 age- and hearing-matched adults to determine the relation between tinnitus characteristics and speech understanding. Further, Tinnitus Handicap Inventory (THI), tinnitus loudness magnitude estimation, and loudness matching were obtained to better characterize the perceptual and psychological aspects of tinnitus. The patients reported low THI scores, with most participants in the slight handicap category. Significant between-group differences in speech-in-noise performance were only found at the 5-dB signal-to-noise ratio (SNR) condition. The tinnitus group performed significantly worse in the left ear than in the right ear, even though bilateral tinnitus percept and symmetrical thresholds were reported in all patients. This between-ear difference is likely influenced by a right-ear advantage for speech sounds, as factors related to testing order and fatigue were ruled out. Additionally, significant correlations found between SNR loss in the left ear and tinnitus loudness matching suggest that perceptual factors related to tinnitus had an effect on speech-in-noise performance, pointing to a possible interaction between peripheral and cognitive factors in chronic tinnitus. Further studies, that take into account both hearing and cognitive abilities of patients, are needed to better parse out the effect of tinnitus in the absence of hearing impairment.

Color Image Secret Watermarking Erase and Write Algorithm Based on SIFT

Science.gov (United States)

Qu, Jubao

The use of adaptive characteristics of SIFT, image features, the implementation of the write, erase operations on Extraction and color image hidden watermarking. From the experimental results, this algorithm has better imperceptibility and at the same time, is robust against geometric attacks and common signal processing.

Ambient analysis of trace compounds in gaseous media by SIFT-MS.

Science.gov (United States)

Smith, David; Spaněl, Patrik

2011-05-21

The topic of ambient gas analysis has been rapidly developed in the last few years with the evolution of the exciting new techniques such as DESI, DART and EESI. The essential feature of all is that analysis of trace gases can be accomplished either in the gas phase or those released from surfaces, crucially avoiding sample collection or modification. In this regard, selected ion flow tube mass spectrometry, SIFT-MS, also performs ambient analyses both accurately and rapidly. In this focused review we describe the underlying ion chemistry underpinning SIFT-MS through a discourse on the reactions of different classes of organic and inorganic molecules with H(3)O(+), NO(+) and O(2)(+)˙ studied using the SIFT technique. Rate coefficients and ion products of these reactions facilitate absolute SIFT-MS analyses and can also be useful for the interpretation of data obtained by the other ambient analysis methods mentioned above. The essential physics and flow dynamics of SIFT-MS are described that, together with the reaction kinetics, allow SIFT-MS to perform absolute ambient analyses of trace compounds in humid atmospheric air, exhaled breath and the headspace of aqueous liquids. Several areas of research that, through pilot experiments, are seen to benefit from ambient gas analysis using SIFT-MS are briefly reviewed. Special attention is given to exhaled breath and urine headspace analysis directed towards clinical diagnosis and therapeutic monitoring, and some other areas researched using SIFT-MS are summarised. Finally, extensions to current areas of application and indications of other directions in which SIFT-MS can be exploited for ambient analysis are alluded to.

An Effective 3D Ear Acquisition System.

Directory of Open Access Journals (Sweden)

Yahui Liu

Full Text Available The human ear is a new feature in biometrics that has several merits over the more common face, fingerprint and iris biometrics. It can be easily captured from a distance without a fully cooperative subject. Also, the ear has a relatively stable structure that does not change much with the age and facial expressions. In this paper, we present a novel method of 3D ear acquisition system by using triangulation imaging principle, and the experiment results show that this design is efficient and can be used for ear recognition.

A MACHINE FOR PULVERIZING AND SIFTING GARI MASH

African Journals Online (AJOL)

Dr Obe

O.75kw electric motor. Fig. 2.Photograph of prototype gari pulverizing/sifting machine. A Side view of the Prototype Gari mash Pulverize/sifting machine. 1. Vee-belt drives; 2. Head pulley; 3 belt conveyor; 4, cake breaker, 5. tail pulley; 6. lump or cake of' gari mash;7hopper; 8pulverizing roller; 9. Side gaurds; 10.brush 11.

Age and gender estimation using Region-SIFT and multi-layered SVM

Science.gov (United States)

Kim, Hyunduk; Lee, Sang-Heon; Sohn, Myoung-Kyu; Hwang, Byunghun

2018-04-01

In this paper, we propose an age and gender estimation framework using the region-SIFT feature and multi-layered SVM classifier. The suggested framework entails three processes. The first step is landmark based face alignment. The second step is the feature extraction step. In this step, we introduce the region-SIFT feature extraction method based on facial landmarks. First, we define sub-regions of the face. We then extract SIFT features from each sub-region. In order to reduce the dimensions of features we employ a Principal Component Analysis (PCA) and a Linear Discriminant Analysis (LDA). Finally, we classify age and gender using a multi-layered Support Vector Machines (SVM) for efficient classification. Rather than performing gender estimation and age estimation independently, the use of the multi-layered SVM can improve the classification rate by constructing a classifier that estimate the age according to gender. Moreover, we collect a dataset of face images, called by DGIST_C, from the internet. A performance evaluation of proposed method was performed with the FERET database, CACD database, and DGIST_C database. The experimental results demonstrate that the proposed approach classifies age and performs gender estimation very efficiently and accurately.

Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction.

Science.gov (United States)

Nguyen, Dat Tien; Kim, Ki Wan; Hong, Hyung Gil; Koo, Ja Hyung; Kim, Min Cheol; Park, Kang Ryoung

2017-03-20

Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images.

Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction

Science.gov (United States)

Nguyen, Dat Tien; Kim, Ki Wan; Hong, Hyung Gil; Koo, Ja Hyung; Kim, Min Cheol; Park, Kang Ryoung

2017-01-01

Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT), speed-up robust feature (SURF), local binary patterns (LBP), histogram of oriented gradients (HOG), and weighted HOG. Recently, the convolutional neural network (CNN) method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images. PMID:28335510

Aggregating Local Descriptors for Epigraphs Recognition

OpenAIRE

Amato, Giuseppe; Falchi, Fabrizio; Rabitti, Fausto; Vadicamo, Lucia

2014-01-01

In this paper, we consider the task of recognizing epigraphs in images such as photos taken using mobile devices. Given a set of 17,155 photos related to 14,560 epigraphs, we used a k-NearestNeighbor approach in order to perform the recognition. The contribution of this work is in evaluating state-of-the-art visual object recognition techniques in this specific context. The experimental results conducted show that Vector of Locally Aggregated Descriptors obtained aggregating SIFT descriptors ...

A novel approach for fire recognition using hybrid features and manifold learning-based classifier

Science.gov (United States)

Zhu, Rong; Hu, Xueying; Tang, Jiajun; Hu, Sheng

2018-03-01

Although image/video based fire recognition has received growing attention, an efficient and robust fire detection strategy is rarely explored. In this paper, we propose a novel approach to automatically identify the flame or smoke regions in an image. It is composed to three stages: (1) a block processing is applied to divide an image into several nonoverlapping image blocks, and these image blocks are identified as suspicious fire regions or not by using two color models and a color histogram-based similarity matching method in the HSV color space, (2) considering that compared to other information, the flame and smoke regions have significant visual characteristics, so that two kinds of image features are extracted for fire recognition, where local features are obtained based on the Scale Invariant Feature Transform (SIFT) descriptor and the Bags of Keypoints (BOK) technique, and texture features are extracted based on the Gray Level Co-occurrence Matrices (GLCM) and the Wavelet-based Analysis (WA) methods, and (3) a manifold learning-based classifier is constructed based on two image manifolds, which is designed via an improve Globular Neighborhood Locally Linear Embedding (GNLLE) algorithm, and the extracted hybrid features are used as input feature vectors to train the classifier, which is used to make decision for fire images or non fire images. Experiments and comparative analyses with four approaches are conducted on the collected image sets. The results show that the proposed approach is superior to the other ones in detecting fire and achieving a high recognition accuracy and a low error rate.

Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach.

Science.gov (United States)

Irshad, Humayun; Jalali, Sepehr; Roux, Ludovic; Racoceanu, Daniel; Hwee, Lim Joo; Naour, Gilles Le; Capron, Frédérique

2013-01-01

According to Nottingham grading system, mitosis count in breast cancer histopathology is one of three components required for cancer grading and prognosis. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. The aim is to investigate the various texture features and Hierarchical Model and X (HMAX) biologically inspired approach for mitosis detection using machine-learning techniques. We propose an approach that assists pathologists in automated mitosis detection and counting. The proposed method, which is based on the most favorable texture features combination, examines the separability between different channels of color space. Blue-ratio channel provides more discriminative information for mitosis detection in histopathological images. Co-occurrence features, run-length features, and Scale-invariant feature transform (SIFT) features were extracted and used in the classification of mitosis. Finally, a classification is performed to put the candidate patch either in the mitosis class or in the non-mitosis class. Three different classifiers have been evaluated: Decision tree, linear kernel Support Vector Machine (SVM), and non-linear kernel SVM. We also evaluate the performance of the proposed framework using the modified biologically inspired model of HMAX and compare the results with other feature extraction methods such as dense SIFT. The proposed method has been tested on Mitosis detection in breast cancer histological images (MITOS) dataset provided for an International Conference on Pattern Recognition (ICPR) 2012 contest. The proposed framework achieved 76% recall, 75% precision and 76% F-measure. Different frameworks for classification have been evaluated for mitosis detection. In future work, instead of regions, we intend to compute features on the results of mitosis contour segmentation and use them to improve detection and classification rate.

Gender Recognition from Human-Body Images Using Visible-Light and Thermal Camera Videos Based on a Convolutional Neural Network for Image Feature Extraction

Directory of Open Access Journals (Sweden)

Dat Tien Nguyen

2017-03-01

Full Text Available Extracting powerful image features plays an important role in computer vision systems. Many methods have previously been proposed to extract image features for various computer vision applications, such as the scale-invariant feature transform (SIFT, speed-up robust feature (SURF, local binary patterns (LBP, histogram of oriented gradients (HOG, and weighted HOG. Recently, the convolutional neural network (CNN method for image feature extraction and classification in computer vision has been used in various applications. In this research, we propose a new gender recognition method for recognizing males and females in observation scenes of surveillance systems based on feature extraction from visible-light and thermal camera videos through CNN. Experimental results confirm the superiority of our proposed method over state-of-the-art recognition methods for the gender recognition problem using human body images.

Robot path Planning Using  SIFT and Sonar Sensor Fusion

DEFF Research Database (Denmark)

Plascencia, Alfredo; Raposo, Hector

2007-01-01

and evidential grid maps, respectively. The approach is illustrated using actual measurements from a laboratory robot. The sensory information is obtained from a sonar array and the Scale Invariant Feature Transform (SIFT) algorithm. Finally, the resulting two evidential maps based on Bayes and Dempster theories...

An Improved SIFT Algorithm for Unmanned Aerial Vehicle Imagery

International Nuclear Information System (INIS)

Li, J M; Yan, D M; Wang, G; Zhang, L

2014-01-01

The Unmanned Aerial Vehicle (UAV) platform has the benefits of low cost and convenience compared with satellites. Recently, UAVs have shown a wide range of applications such as land use change, mineral resources management and local topographic mapping. Because of the instability of the UAV air gesture, an image matching method is necessary to match different images of an object or scene. Scale Invariant Feature Transform (SIFT) features are invariant to image scaling, rotation and translation. However, the main drawback of a SIFT algorithm is its significant memory consumption and low computational speed, particularly in the case of high-resolution imagery. In this study, in order to overcome these drawbacks, we have analysed the construction of the scale-space in the SIFT algorithm and selected new parameters to construct the SIFT scale-space to improve the memory consumption and computational speed for the processing of UAV imagery. Here, we propose a restriction on the number of octaves and levels for Gaussian image pyramids. Our experiment shows that the proposed algorithm effectively reduces memory consumption and significantly improves the operational efficiency of the feature point extraction and matching under the premise of maintaining the precision of the extracted feature points

MBR-SIFT: A mirror reflected invariant feature descriptor using a binary representation for image matching.

Directory of Open Access Journals (Sweden)

Mingzhe Su

Full Text Available The traditional scale invariant feature transform (SIFT method can extract distinctive features for image matching. However, it is extremely time-consuming in SIFT matching because of the use of the Euclidean distance measure. Recently, many binary SIFT (BSIFT methods have been developed to improve matching efficiency; however, none of them is invariant to mirror reflection. To address these problems, in this paper, we present a horizontal or vertical mirror reflection invariant binary descriptor named MBR-SIFT, in addition to a novel image matching approach. First, 16 cells in the local region around the SIFT keypoint are reorganized, and then the 128-dimensional vector of the SIFT descriptor is transformed into a reconstructed vector according to eight directions. Finally, the MBR-SIFT descriptor is obtained after binarization and reverse coding. To improve the matching speed and accuracy, a fast matching algorithm that includes a coarse-to-fine two-step matching strategy in addition to two similarity measures for the MBR-SIFT descriptor are proposed. Experimental results on the UKBench dataset show that the proposed method not only solves the problem of mirror reflection, but also ensures desirable matching accuracy and speed.

MBR-SIFT: A mirror reflected invariant feature descriptor using a binary representation for image matching.

Science.gov (United States)

Su, Mingzhe; Ma, Yan; Zhang, Xiangfen; Wang, Yan; Zhang, Yuping

2017-01-01

The traditional scale invariant feature transform (SIFT) method can extract distinctive features for image matching. However, it is extremely time-consuming in SIFT matching because of the use of the Euclidean distance measure. Recently, many binary SIFT (BSIFT) methods have been developed to improve matching efficiency; however, none of them is invariant to mirror reflection. To address these problems, in this paper, we present a horizontal or vertical mirror reflection invariant binary descriptor named MBR-SIFT, in addition to a novel image matching approach. First, 16 cells in the local region around the SIFT keypoint are reorganized, and then the 128-dimensional vector of the SIFT descriptor is transformed into a reconstructed vector according to eight directions. Finally, the MBR-SIFT descriptor is obtained after binarization and reverse coding. To improve the matching speed and accuracy, a fast matching algorithm that includes a coarse-to-fine two-step matching strategy in addition to two similarity measures for the MBR-SIFT descriptor are proposed. Experimental results on the UKBench dataset show that the proposed method not only solves the problem of mirror reflection, but also ensures desirable matching accuracy and speed.

Are two ears not better than one?

Science.gov (United States)

McArdle, Rachel A; Killion, Mead; Mennite, Monica A; Chisolm, Theresa H

2012-03-01

The decision to fit one or two hearing aids in individuals with binaural hearing loss has been debated for years. Although some 78% of U.S. hearing aid fittings are binaural (Kochkin , 2010), Walden and Walden (2005) presented data showing that 82% (23 of 28 patients) of their sample obtained significantly better speech recognition in noise scores when wearing one hearing aid as opposed to two. To conduct two new experiments to fuel the monaural/binaural debate. The first experiment was a replication of Walden and Walden (2005), whereas the second experiment examined the use of binaural cues to improve speech recognition in noise. A repeated measures experimental design. Twenty veterans (aged 59-85 yr), with mild to moderately severe binaurally symmetrical hearing loss who wore binaural hearing aids were recruited from the Audiology Department at the Bay Pines VA Healthcare System. Experiment 1 followed the procedures of the Walden and Walden study, where signal-to-noise ratio (SNR) loss was measured using the Quick Speech-in-Noise (QuickSIN) test on participants who were aided with their current hearing aids. Signal and noise were presented in the sound booth at 0° azimuth under five test conditions: (1) right ear aided, (2) left ear aided, (3) both ears aided, (4) right ear aided, left ear plugged, and (5) unaided. The opposite ear in (1) and (2) was left open. In Experiment 2, binaural Knowles Electronics Manikin for Acoustic Research (KEMAR) manikin recordings made in Lou Malnati's pizza restaurant during a busy period provided a typical real-world noise, while prerecorded target sentences were presented through a small loudspeaker located in front of the KEMAR manikin. Subjects listened to the resulting binaural recordings through insert earphones under the following four conditions: (1) binaural, (2) diotic, (3) monaural left, and (4) monaural right. Results of repeated measures ANOVAs demonstrated that the best speech recognition in noise performance was

An Efficient Multimodal 2D + 3D Feature-based Approach to Automatic Facial Expression Recognition

KAUST Repository

Li, Huibin

2015-07-29

We present a fully automatic multimodal 2D + 3D feature-based facial expression recognition approach and demonstrate its performance on the BU-3DFE database. Our approach combines multi-order gradient-based local texture and shape descriptors in order to achieve efficiency and robustness. First, a large set of fiducial facial landmarks of 2D face images along with their 3D face scans are localized using a novel algorithm namely incremental Parallel Cascade of Linear Regression (iPar-CLR). Then, a novel Histogram of Second Order Gradients (HSOG) based local image descriptor in conjunction with the widely used first-order gradient based SIFT descriptor are used to describe the local texture around each 2D landmark. Similarly, the local geometry around each 3D landmark is described by two novel local shape descriptors constructed using the first-order and the second-order surface differential geometry quantities, i.e., Histogram of mesh Gradients (meshHOG) and Histogram of mesh Shape index (curvature quantization, meshHOS). Finally, the Support Vector Machine (SVM) based recognition results of all 2D and 3D descriptors are fused at both feature-level and score-level to further improve the accuracy. Comprehensive experimental results demonstrate that there exist impressive complementary characteristics between the 2D and 3D descriptors. We use the BU-3DFE benchmark to compare our approach to the state-of-the-art ones. Our multimodal feature-based approach outperforms the others by achieving an average recognition accuracy of 86.32%. Moreover, a good generalization ability is shown on the Bosphorus database.

An Efficient Multimodal 2D + 3D Feature-based Approach to Automatic Facial Expression Recognition

KAUST Repository

Li, Huibin; Ding, Huaxiong; Huang, Di; Wang, Yunhong; Zhao, Xi; Morvan, Jean-Marie; Chen, Liming

2015-01-01

We present a fully automatic multimodal 2D + 3D feature-based facial expression recognition approach and demonstrate its performance on the BU-3DFE database. Our approach combines multi-order gradient-based local texture and shape descriptors in order to achieve efficiency and robustness. First, a large set of fiducial facial landmarks of 2D face images along with their 3D face scans are localized using a novel algorithm namely incremental Parallel Cascade of Linear Regression (iPar-CLR). Then, a novel Histogram of Second Order Gradients (HSOG) based local image descriptor in conjunction with the widely used first-order gradient based SIFT descriptor are used to describe the local texture around each 2D landmark. Similarly, the local geometry around each 3D landmark is described by two novel local shape descriptors constructed using the first-order and the second-order surface differential geometry quantities, i.e., Histogram of mesh Gradients (meshHOG) and Histogram of mesh Shape index (curvature quantization, meshHOS). Finally, the Support Vector Machine (SVM) based recognition results of all 2D and 3D descriptors are fused at both feature-level and score-level to further improve the accuracy. Comprehensive experimental results demonstrate that there exist impressive complementary characteristics between the 2D and 3D descriptors. We use the BU-3DFE benchmark to compare our approach to the state-of-the-art ones. Our multimodal feature-based approach outperforms the others by achieving an average recognition accuracy of 86.32%. Moreover, a good generalization ability is shown on the Bosphorus database.

Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach

Directory of Open Access Journals (Sweden)

Humayun Irshad

2013-01-01

Full Text Available Context: According to Nottingham grading system, mitosis count in breast cancer histopathology is one of three components required for cancer grading and prognosis. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. Aims: The aim is to investigate the various texture features and Hierarchical Model and X (HMAX biologically inspired approach for mitosis detection using machine-learning techniques. Materials and Methods: We propose an approach that assists pathologists in automated mitosis detection and counting. The proposed method, which is based on the most favorable texture features combination, examines the separability between different channels of color space. Blue-ratio channel provides more discriminative information for mitosis detection in histopathological images. Co-occurrence features, run-length features, and Scale-invariant feature transform (SIFT features were extracted and used in the classification of mitosis. Finally, a classification is performed to put the candidate patch either in the mitosis class or in the non-mitosis class. Three different classifiers have been evaluated: Decision tree, linear kernel Support Vector Machine (SVM, and non-linear kernel SVM. We also evaluate the performance of the proposed framework using the modified biologically inspired model of HMAX and compare the results with other feature extraction methods such as dense SIFT. Results: The proposed method has been tested on Mitosis detection in breast cancer histological images (MITOS dataset provided for an International Conference on Pattern Recognition (ICPR 2012 contest. The proposed framework achieved 76% recall, 75% precision and 76% F-measure. Conclusions: Different frameworks for classification have been evaluated for mitosis detection. In future work, instead of regions, we intend to compute features on the results of mitosis contour segmentation and use them to improve detection and

Quality of the oriental fruit fly, bactrocera dorsalis (Hendel) after sifting pupae by mechanical sifter

International Nuclear Information System (INIS)

Sutantawong, M.; Uthaisarn, K.

1996-01-01

Quality of fruit fly, bactrocera dorsalis (Hendel) in mass production is important for controlling pest populations by means of the sterile insect technique. The experiment was to study the quality of fruit fly after sifting pupae by mechanical sifter. Laboratory-reared pupae, held at 26 ± 1 degree C were sifted at intensity of 18 rpm in a rotary sifting device at 1, 2, 3, 4, 5, 6, 7 and 8 days of age. The quality of fruit flies were determined on adult eclosion and flight capability. The results showed that there were no significantly different (P < 0.05) in adult eclosion between control with sifted pupae at 1 to 8 days of age. However, there were significantly different (P < 0.05) in flight capability between control and sifted pupae at 1, 5, 6, 7, 8 days of age with sifted pupae at 2, 3, 4 days of age

Structural Metadata Research in the Ears Program

National Research Council Canada - National Science Library

Liu, Yang; Shriberg, Elizabeth; Stolcke, Andreas; Peskin, Barbara; Ang, Jeremy; Hillard, Dustin; Ostendorf, Mari; Tomalin, Marcus; Woodland, Phil; Harper, Mary

2005-01-01

Both human and automatic processing of speech require recognition of more than just words. In this paper we provide a brief overview of research on structural metadata extraction in the DARPA EARS rich transcription program...

An assessment of the real-time application capabilities of the SIFT computer system

Science.gov (United States)

Butler, R. W.

1982-01-01

The real-time capabilities of the SIFT computer system, a highly reliable multicomputer architecture developed to support the flight controls of a relaxed static stability aircraft, are discussed. The SIFT computer system was designed to meet extremely high reliability requirements and to facilitate a formal proof of its correctness. Although SIFT represents a significant achievement in fault-tolerant system research it presents an unusual and restrictive interface to its users. The characteristics of the user interface and its impact on application system design are assessed.

Performance Analysis of the SIFT Operator for Automatic Feature Extraction and Matching in Photogrammetric Applications

Directory of Open Access Journals (Sweden)

Francesco Nex

2009-05-01

Full Text Available In the photogrammetry field, interest in region detectors, which are widely used in Computer Vision, is quickly increasing due to the availability of new techniques. Images acquired by Mobile Mapping Technology, Oblique Photogrammetric Cameras or Unmanned Aerial Vehicles do not observe normal acquisition conditions. Feature extraction and matching techniques, which are traditionally used in photogrammetry, are usually inefficient for these applications as they are unable to provide reliable results under extreme geometrical conditions (convergent taking geometry, strong affine transformations, etc. and for bad-textured images. A performance analysis of the SIFT technique in aerial and close-range photogrammetric applications is presented in this paper. The goal is to establish the suitability of the SIFT technique for automatic tie point extraction and approximate DSM (Digital Surface Model generation. First, the performances of the SIFT operator have been compared with those provided by feature extraction and matching techniques used in photogrammetry. All these techniques have been implemented by the authors and validated on aerial and terrestrial images. Moreover, an auto-adaptive version of the SIFT operator has been developed, in order to improve the performances of the SIFT detector in relation to the texture of the images. The Auto-Adaptive SIFT operator (A2 SIFT has been validated on several aerial images, with particular attention to large scale aerial images acquired using mini-UAV systems.

Middle ear osteoma causing progressive facial nerve weakness: a case report.

Science.gov (United States)

Curtis, Kate; Bance, Manohar; Carter, Michael; Hong, Paul

2014-09-18

Facial nerve weakness is most commonly due to Bell's palsy or cerebrovascular accidents. Rarely, middle ear tumor presents with facial nerve dysfunction. We report a very unusual case of middle ear osteoma in a 49-year-old Caucasian woman causing progressive facial nerve deficit. A subtle middle ear lesion was observed on otoscopy and computed tomographic images demonstrated an osseous middle ear tumor. Complete surgical excision resulted in the partial recovery of facial nerve function. Facial nerve dysfunction is rarely caused by middle ear tumors. The weakness is typically due to a compressive effect on the middle ear portion of the facial nerve. Early recognition is crucial since removal of these lesions may lead to the recuperation of facial nerve function.

Ear examination

Science.gov (United States)

... may be present. The eardrum is a light-gray color or a shiny pearly-white. Light should ... discharge or bleeding Alternative Names Otoscopy Images Ear anatomy Medical findings based on ear anatomy Otoscopic exam ...

Improving Measurement Efficiency of the Inner EAR Scale with Item Response Theory.

Science.gov (United States)

Jessen, Annika; Ho, Andrew D; Corrales, C Eduardo; Yueh, Bevan; Shin, Jennifer J

2018-02-01

Objectives (1) To assess the 11-item Inner Effectiveness of Auditory Rehabilitation (Inner EAR) instrument with item response theory (IRT). (2) To determine whether the underlying latent ability could also be accurately represented by a subset of the items for use in high-volume clinical scenarios. (3) To determine whether the Inner EAR instrument correlates with pure tone thresholds and word recognition scores. Design IRT evaluation of prospective cohort data. Setting Tertiary care academic ambulatory otolaryngology clinic. Subjects and Methods Modern psychometric methods, including factor analysis and IRT, were used to assess unidimensionality and item properties. Regression methods were used to assess prediction of word recognition and pure tone audiometry scores. Results The Inner EAR scale is unidimensional, and items varied in their location and information. Information parameter estimates ranged from 1.63 to 4.52, with higher values indicating more useful items. The IRT model provided a basis for identifying 2 sets of items with relatively lower information parameters. Item information functions demonstrated which items added insubstantial value over and above other items and were removed in stages, creating a 8- and 3-item Inner EAR scale for more efficient assessment. The 8-item version accurately reflected the underlying construct. All versions correlated moderately with word recognition scores and pure tone averages. Conclusion The 11-, 8-, and 3-item versions of the Inner EAR scale have strong psychometric properties, and there is correlational validity evidence for the observed scores. Modern psychometric methods can help streamline care delivery by maximizing relevant information per item administered.

Lessons Sifted from Tragedy at Columbine

Science.gov (United States)

Viadero, Debra

2009-01-01

A decade after Eric D. Harris and Dylan B. Klebold fatally gunned down 13 people and wounded 23 others at Columbine High School, researchers are still sifting for answers to questions raised by the elaborate and notorious attack. Books and studies being published to coincide with the 10th anniversary of the April 20, 1999, massacre at the…

Sensor Fusion - Sonar and Stereo Vision, Using Occupancy Grids and SIFT

DEFF Research Database (Denmark)

Plascencia, Alfredo; Bendtsen, Jan Dimon

2006-01-01

to the occupied and empty regions. SIFT (Scale Invariant Feature Transform) feature descriptors are  interpreted using gaussian probabilistic error models. The use of occupancy grids is proposed for representing the sonar  as well as the features descriptors readings. The Bayesian estimation approach is applied...... to update the sonar and the SIFT descriptors' uncertainty grids. The sensor fusion yields a significant reduction in the uncertainty of the occupancy grid compared to the individual sensor readings....

Morphology and Efficiency of a Specialized Foraging Behavior, Sediment Sifting, in Neotropical Cichlid Fishes

Science.gov (United States)

Willis, Stuart; Watkins, Crystal; Honeycutt, Rodney L.; Winemiller, Kirk O.

2014-01-01

Understanding of relationships between morphology and ecological performance can help to reveal how natural selection drives biological diversification. We investigate relationships between feeding behavior, foraging performance and morphology within a diverse group of teleost fishes, and examine the extent to which associations can be explained by evolutionary relatedness. Morphological adaptation associated with sediment sifting was examined using a phylogenetic linear discriminant analysis on a set of ecomorphological traits from 27 species of Neotropical cichlids. For most sifting taxa, feeding behavior could be effectively predicted by a linear discriminant function of ecomorphology across multiple clades of sediment sifters, and this pattern could not be explained by shared evolutionary history alone. Additionally, we tested foraging efficiency in seven Neotropical cichlid species, five of which are specialized benthic feeders with differing head morphology. Efficiency was evaluated based on the degree to which invertebrate prey could be retrieved at different depths of sediment. Feeding performance was compared both with respect to feeding mode and species using a phylogenetic ANCOVA, with substrate depth as a covariate. Benthic foraging performance was constant across sediment depths in non-sifters but declined with depth in sifters. The non-sifting Hypsophrys used sweeping motions of the body and fins to excavate large pits to uncover prey; this tactic was more efficient for consuming deeply buried invertebrates than observed among sediment sifters. Findings indicate that similar feeding performance among sediment-sifting cichlids extracting invertebrate prey from shallow sediment layers reflects constraints associated with functional morphology and, to a lesser extent, phylogeny. PMID:24603485

Morphology and efficiency of a specialized foraging behavior, sediment sifting, in neotropical cichlid fishes.

Directory of Open Access Journals (Sweden)

Hernán López-Fernández

Full Text Available Understanding of relationships between morphology and ecological performance can help to reveal how natural selection drives biological diversification. We investigate relationships between feeding behavior, foraging performance and morphology within a diverse group of teleost fishes, and examine the extent to which associations can be explained by evolutionary relatedness. Morphological adaptation associated with sediment sifting was examined using a phylogenetic linear discriminant analysis on a set of ecomorphological traits from 27 species of Neotropical cichlids. For most sifting taxa, feeding behavior could be effectively predicted by a linear discriminant function of ecomorphology across multiple clades of sediment sifters, and this pattern could not be explained by shared evolutionary history alone. Additionally, we tested foraging efficiency in seven Neotropical cichlid species, five of which are specialized benthic feeders with differing head morphology. Efficiency was evaluated based on the degree to which invertebrate prey could be retrieved at different depths of sediment. Feeding performance was compared both with respect to feeding mode and species using a phylogenetic ANCOVA, with substrate depth as a covariate. Benthic foraging performance was constant across sediment depths in non-sifters but declined with depth in sifters. The non-sifting Hypsophrys used sweeping motions of the body and fins to excavate large pits to uncover prey; this tactic was more efficient for consuming deeply buried invertebrates than observed among sediment sifters. Findings indicate that similar feeding performance among sediment-sifting cichlids extracting invertebrate prey from shallow sediment layers reflects constraints associated with functional morphology and, to a lesser extent, phylogeny.

Morphology and efficiency of a specialized foraging behavior, sediment sifting, in neotropical cichlid fishes.

Science.gov (United States)

López-Fernández, Hernán; Arbour, Jessica; Willis, Stuart; Watkins, Crystal; Honeycutt, Rodney L; Winemiller, Kirk O

2014-01-01

Understanding of relationships between morphology and ecological performance can help to reveal how natural selection drives biological diversification. We investigate relationships between feeding behavior, foraging performance and morphology within a diverse group of teleost fishes, and examine the extent to which associations can be explained by evolutionary relatedness. Morphological adaptation associated with sediment sifting was examined using a phylogenetic linear discriminant analysis on a set of ecomorphological traits from 27 species of Neotropical cichlids. For most sifting taxa, feeding behavior could be effectively predicted by a linear discriminant function of ecomorphology across multiple clades of sediment sifters, and this pattern could not be explained by shared evolutionary history alone. Additionally, we tested foraging efficiency in seven Neotropical cichlid species, five of which are specialized benthic feeders with differing head morphology. Efficiency was evaluated based on the degree to which invertebrate prey could be retrieved at different depths of sediment. Feeding performance was compared both with respect to feeding mode and species using a phylogenetic ANCOVA, with substrate depth as a covariate. Benthic foraging performance was constant across sediment depths in non-sifters but declined with depth in sifters. The non-sifting Hypsophrys used sweeping motions of the body and fins to excavate large pits to uncover prey; this tactic was more efficient for consuming deeply buried invertebrates than observed among sediment sifters. Findings indicate that similar feeding performance among sediment-sifting cichlids extracting invertebrate prey from shallow sediment layers reflects constraints associated with functional morphology and, to a lesser extent, phylogeny.

Expression robust 3D face recognition via mesh-based histograms of multiple order surface differential quantities

KAUST Repository

Li, Huibin

2011-09-01

This paper presents a mesh-based approach for 3D face recognition using a novel local shape descriptor and a SIFT-like matching process. Both maximum and minimum curvatures estimated in the 3D Gaussian scale space are employed to detect salient points. To comprehensively characterize 3D facial surfaces and their variations, we calculate weighted statistical distributions of multiple order surface differential quantities, including histogram of mesh gradient (HoG), histogram of shape index (HoS) and histogram of gradient of shape index (HoGS) within a local neighborhood of each salient point. The subsequent matching step then robustly associates corresponding points of two facial surfaces, leading to much more matched points between different scans of a same person than the ones of different persons. Experimental results on the Bosphorus dataset highlight the effectiveness of the proposed method and its robustness to facial expression variations. © 2011 IEEE.

EARS: An Online Bibliographic Search and Retrieval System Based on Ordered Explosion.

Science.gov (United States)

Ramesh, R.; Drury, Colin G.

1987-01-01

Provides overview of Ergonomics Abstracts Retrieval System (EARS), an online bibliographic search and retrieval system in the area of human factors engineering. Other online systems are described, the design of EARS based on inverted file organization is explained, and system expansions including a thesaurus are discussed. (Author/LRW)

Sifting through genomes with iterative-sequence clustering produces a large, phylogenetically diverse protein-family resource.

Science.gov (United States)

Sharpton, Thomas J; Jospin, Guillaume; Wu, Dongying; Langille, Morgan G I; Pollard, Katherine S; Eisen, Jonathan A

2012-10-13

New computational resources are needed to manage the increasing volume of biological data from genome sequencing projects. One fundamental challenge is the ability to maintain a complete and current catalog of protein diversity. We developed a new approach for the identification of protein families that focuses on the rapid discovery of homologous protein sequences. We implemented fully automated and high-throughput procedures to de novo cluster proteins into families based upon global alignment similarity. Our approach employs an iterative clustering strategy in which homologs of known families are sifted out of the search for new families. The resulting reduction in computational complexity enables us to rapidly identify novel protein families found in new genomes and to perform efficient, automated updates that keep pace with genome sequencing. We refer to protein families identified through this approach as "Sifting Families," or SFams. Our analysis of ~10.5 million protein sequences from 2,928 genomes identified 436,360 SFams, many of which are not represented in other protein family databases. We validated the quality of SFam clustering through statistical as well as network topology-based analyses. We describe the rapid identification of SFams and demonstrate how they can be used to annotate genomes and metagenomes. The SFam database catalogs protein-family quality metrics, multiple sequence alignments, hidden Markov models, and phylogenetic trees. Our source code and database are publicly available and will be subject to frequent updates (http://edhar.genomecenter.ucdavis.edu/sifting_families/).

A Selected Ion Flow Tube, SIFT, Study of the Reactions of H3O+, NO+ and O2+·áIons with Several N- and O-containing Heterocyclic Compounds in Support of SIFT-MS

Czech Academy of Sciences Publication Activity Database

Wang, T.; Smith, D.; Španěl, Patrik

2004-01-01

Roč. 237, č. 1 (2004), s. 167-174 ISSN 1387-3806 R&D Projects: GA ČR GA202/03/0827; GA ČR GA203/02/0737 Institutional research plan: CEZ:AV0Z4040901 Keywords : SIFT * heterocyclic s * SIFT-MS Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.235, year: 2004

Multiscale registration of remote sensing image using robust SIFT features in Steerable-Domain

Directory of Open Access Journals (Sweden)

Xiangzeng Liu

2011-12-01

Full Text Available This paper proposes a multiscale registration technique using robust Scale Invariant Feature Transform (SIFT features in Steerable-Domain, which can deal with the large variations of scale, rotation and illumination between images. First, a new robust SIFT descriptor is presented, which is invariant under affine transformation. Then, an adaptive similarity measure is developed according to the robust SIFT descriptor and the adaptive normalized cross correlation of feature point’s neighborhood. Finally, the corresponding feature points can be determined by the adaptive similarity measure in Steerable-Domain of the two input images, and the final refined transformation parameters determined by using gradual optimization are adopted to achieve the registration results. Quantitative comparisons of our algorithm with the related methods show a significant improvement in the presence of large scale, rotation changes, and illumination contrast. The effectiveness of the proposed method is demonstrated by the experimental results.

Development of Neuromorphic Sift Operator with Application to High Speed Image Matching

Science.gov (United States)

Shankayi, M.; Saadatseresht, M.; Bitetto, M. A. V.

2015-12-01

There was always a speed/accuracy challenge in photogrammetric mapping process, including feature detection and matching. Most of the researches have improved algorithm's speed with simplifications or software modifications which increase the accuracy of the image matching process. This research tries to improve speed without enhancing the accuracy of the same algorithm using Neuromorphic techniques. In this research we have developed a general design of a Neuromorphic ASIC to handle algorithms such as SIFT. We also have investigated neural assignment in each step of the SIFT algorithm. With a rough estimation based on delay of the used elements including MAC and comparator, we have estimated the resulting chip's performance for 3 scenarios, Full HD movie (Videogrammetry), 24 MP (UAV photogrammetry), and 88 MP image sequence. Our estimations led to approximate 3000 fps for Full HD movie, 250 fps for 24 MP image sequence and 68 fps for 88MP Ultracam image sequence which can be a huge improvement for current photogrammetric processing systems. We also estimated the power consumption of less than10 watts which is not comparable to current workflows.

Image stack alignment in full-field X-ray absorption spectroscopy using SIFT_PyOCL.

Science.gov (United States)

Paleo, Pierre; Pouyet, Emeline; Kieffer, Jérôme

2014-03-01

Full-field X-ray absorption spectroscopy experiments allow the acquisition of millions of spectra within minutes. However, the construction of the hyperspectral image requires an image alignment procedure with sub-pixel precision. While the image correlation algorithm has originally been used for image re-alignment using translations, the Scale Invariant Feature Transform (SIFT) algorithm (which is by design robust versus rotation, illumination change, translation and scaling) presents an additional advantage: the alignment can be limited to a region of interest of any arbitrary shape. In this context, a Python module, named SIFT_PyOCL, has been developed. It implements a parallel version of the SIFT algorithm in OpenCL, providing high-speed image registration and alignment both on processors and graphics cards. The performance of the algorithm allows online processing of large datasets.

Speech recognition in individuals with sensorineural hearing loss

Directory of Open Access Journals (Sweden)

Adriana Neves de Andrade

Full Text Available ABSTRACT INTRODUCTION: Hearing loss can negatively influence the communication performance of individuals, who should be evaluated with suitable material and in situations of listening close to those found in everyday life. OBJECTIVE: To analyze and compare the performance of patients with mild-to-moderate sensorineural hearing loss in speech recognition tests carried out in silence and with noise, according to the variables ear (right and left and type of stimulus presentation. METHODS: The study included 19 right-handed individuals with mild-to-moderate symmetrical bilateral sensorineural hearing loss, submitted to the speech recognition test with words in different modalities and speech test with white noise and pictures. RESULTS: There was no significant difference between right and left ears in any of the tests. The mean number of correct responses in the speech recognition test with pictures, live voice, and recorded monosyllables was 97.1%, 85.9%, and 76.1%, respectively, whereas after the introduction of noise, the performance decreased to 72.6% accuracy. CONCLUSIONS: The best performances in the Speech Recognition Percentage Index were obtained using monosyllabic stimuli, represented by pictures presented in silence, with no significant differences between the right and left ears. After the introduction of competitive noise, there was a decrease in individuals' performance.

Sifting through genomes with iterative-sequence clustering produces a large, phylogenetically diverse protein-family resource

Directory of Open Access Journals (Sweden)

Sharpton Thomas J

2012-10-01

Full Text Available Abstract Background New computational resources are needed to manage the increasing volume of biological data from genome sequencing projects. One fundamental challenge is the ability to maintain a complete and current catalog of protein diversity. We developed a new approach for the identification of protein families that focuses on the rapid discovery of homologous protein sequences. Results We implemented fully automated and high-throughput procedures to de novo cluster proteins into families based upon global alignment similarity. Our approach employs an iterative clustering strategy in which homologs of known families are sifted out of the search for new families. The resulting reduction in computational complexity enables us to rapidly identify novel protein families found in new genomes and to perform efficient, automated updates that keep pace with genome sequencing. We refer to protein families identified through this approach as “Sifting Families,” or SFams. Our analysis of ~10.5 million protein sequences from 2,928 genomes identified 436,360 SFams, many of which are not represented in other protein family databases. We validated the quality of SFam clustering through statistical as well as network topology–based analyses. Conclusions We describe the rapid identification of SFams and demonstrate how they can be used to annotate genomes and metagenomes. The SFam database catalogs protein-family quality metrics, multiple sequence alignments, hidden Markov models, and phylogenetic trees. Our source code and database are publicly available and will be subject to frequent updates (http://edhar.genomecenter.ucdavis.edu/sifting_families/.

A self-teaching image processing and voice-recognition-based, intelligent and interactive system to educate visually impaired children

Science.gov (United States)

Iqbal, Asim; Farooq, Umar; Mahmood, Hassan; Asad, Muhammad Usman; Khan, Akrama; Atiq, Hafiz Muhammad

2010-02-01

A self teaching image processing and voice recognition based system is developed to educate visually impaired children, chiefly in their primary education. System comprises of a computer, a vision camera, an ear speaker and a microphone. Camera, attached with the computer system is mounted on the ceiling opposite (on the required angle) to the desk on which the book is placed. Sample images and voices in the form of instructions and commands of English, Urdu alphabets, Numeric Digits, Operators and Shapes are already stored in the database. A blind child first reads the embossed character (object) with the help of fingers than he speaks the answer, name of the character, shape etc into the microphone. With the voice command of a blind child received by the microphone, image is taken by the camera which is processed by MATLAB® program developed with the help of Image Acquisition and Image processing toolbox and generates a response or required set of instructions to child via ear speaker, resulting in self education of a visually impaired child. Speech recognition program is also developed in MATLAB® with the help of Data Acquisition and Signal Processing toolbox which records and process the command of the blind child.

Statistical Shape Analysis of the Human Ear Canal with Application to In-the-Ear Hearing Aid Design

DEFF Research Database (Denmark)

Paulsen, Rasmus Reinhold

2004-01-01

This thesis is about the statistical shape analysis of the human ear canal with application to the mechanical design of in-the-ear hearing aids. Initially, it is described how a statistical shape model of the human ear canal is built based on a training set of laser-scanned ear impressions. A thin...

Ear Infection (Middle Ear)

Science.gov (United States)

... secretions from the middle ear Swelling, inflammation and mucus in the eustachian tubes from an upper respiratory ... your baby for at least six months. Breast milk contains antibodies that may offer protection from ear ...

Improved Feature Detection in Fused Intensity-Range Images with Complex SIFT (ℂSIFT

Directory of Open Access Journals (Sweden)

Boris Jutzi

2011-09-01

Full Text Available The real and imaginary parts are proposed as an alternative to the usual Polar representation of complex-valued images. It is proven that the transformation from Polar to Cartesian representation contributes to decreased mutual information, and hence to greater distinctiveness. The Complex Scale-Invariant Feature Transform (ℂSIFT detects distinctive features in complex-valued images. An evaluation method for estimating the uniformity of feature distributions in complex-valued images derived from intensity-range images is proposed. In order to experimentally evaluate the proposed methodology on intensity-range images, three different kinds of active sensing systems were used: Range Imaging, Laser Scanning, and Structured Light Projection devices (PMD CamCube 2.0, Z+F IMAGER 5003, Microsoft Kinect.

Speech recognition in individuals with sensorineural hearing loss.

Science.gov (United States)

de Andrade, Adriana Neves; Iorio, Maria Cecilia Martinelli; Gil, Daniela

2016-01-01

Hearing loss can negatively influence the communication performance of individuals, who should be evaluated with suitable material and in situations of listening close to those found in everyday life. To analyze and compare the performance of patients with mild-to-moderate sensorineural hearing loss in speech recognition tests carried out in silence and with noise, according to the variables ear (right and left) and type of stimulus presentation. The study included 19 right-handed individuals with mild-to-moderate symmetrical bilateral sensorineural hearing loss, submitted to the speech recognition test with words in different modalities and speech test with white noise and pictures. There was no significant difference between right and left ears in any of the tests. The mean number of correct responses in the speech recognition test with pictures, live voice, and recorded monosyllables was 97.1%, 85.9%, and 76.1%, respectively, whereas after the introduction of noise, the performance decreased to 72.6% accuracy. The best performances in the Speech Recognition Percentage Index were obtained using monosyllabic stimuli, represented by pictures presented in silence, with no significant differences between the right and left ears. After the introduction of competitive noise, there was a decrease in individuals' performance. Copyright © 2015 Associação Brasileira de Otorrinolaringologia e Cirurgia Cérvico-Facial. Published by Elsevier Editora Ltda. All rights reserved.

An Optimized Structure on FPGA of Key Point Detection in SIFT Algorithm

Directory of Open Access Journals (Sweden)

Xu Chenyu

2016-01-01

Full Text Available SIFT algorithm is the most efficient and powerful algorithm to describe the features of images and it has been applied in many fields. In this paper, we propose an optimized method to realize the hardware implementation of the SIFT algorithm. We mainly discuss the structure of Data Generation here. A pipeline architecture is introduced to accelerate this optimized system. Parameters’ setting and approximation’s controlling in different image qualities and hardware resources are the focus of this paper. The results of experiments fully prove that this structure is real-time and effective, and provide consultative opinion to meet the different situations.

Ear Injury

Science.gov (United States)

... of different injuries can affect the outer ear. Cauliflower ear (subperichondrial hematoma) A blunt blow to the ... to a deformed ear. This deformity, called a cauliflower ear, is common among wrestlers, boxers, and rugby ...

Eye movement analysis for activity recognition using electrooculography.

Science.gov (United States)

Bulling, Andreas; Ward, Jamie A; Gellersen, Hans; Tröster, Gerhard

2011-04-01

In this work, we investigate eye movement analysis as a new sensing modality for activity recognition. Eye movement data were recorded using an electrooculography (EOG) system. We first describe and evaluate algorithms for detecting three eye movement characteristics from EOG signals-saccades, fixations, and blinks-and propose a method for assessing repetitive patterns of eye movements. We then devise 90 different features based on these characteristics and select a subset of them using minimum redundancy maximum relevance (mRMR) feature selection. We validate the method using an eight participant study in an office environment using an example set of five activity classes: copying a text, reading a printed paper, taking handwritten notes, watching a video, and browsing the Web. We also include periods with no specific activity (the NULL class). Using a support vector machine (SVM) classifier and person-independent (leave-one-person-out) training, we obtain an average precision of 76.1 percent and recall of 70.5 percent over all classes and participants. The work demonstrates the promise of eye-based activity recognition (EAR) and opens up discussion on the wider applicability of EAR to other activities that are difficult, or even impossible, to detect using common sensing modalities.

Recognition of Faces in Unconstrained Environments: A Comparative Study

Directory of Open Access Journals (Sweden)

Javier Ruiz-del-Solar

2009-01-01

Full Text Available The aim of this work is to carry out a comparative study of face recognition methods that are suitable to work in unconstrained environments. The analyzed methods are selected by considering their performance in former comparative studies, in addition to be real-time, to require just one image per person, and to be fully online. In the study two local-matching methods, histograms of LBP features and Gabor Jet descriptors, one holistic method, generalized PCA, and two image-matching methods, SIFT-based and ERCF-based, are analyzed. The methods are compared using the FERET, LFW, UCHFaceHRI, and FRGC databases, which allows evaluating them in real-world conditions that include variations in scale, pose, lighting, focus, resolution, facial expression, accessories, makeup, occlusions, background and photographic quality. Main conclusions of this study are: there is a large dependence of the methods on the amount of face and background information that is included in the face's images, and the performance of all methods decreases largely with outdoor-illumination. The analyzed methods are robust to inaccurate alignment, face occlusions, and variations in expressions, to a large degree. LBP-based methods are an excellent election if we need real-time operation as well as high recognition rates.

Towards 3D Face Recognition in the Real: A Registration-Free Approach Using Fine-Grained Matching of 3D Keypoint Descriptors

KAUST Repository

Li, Huibin

2014-11-12

Registration algorithms performed on point clouds or range images of face scans have been successfully used for automatic 3D face recognition under expression variations, but have rarely been investigated to solve pose changes and occlusions mainly since that the basic landmarks to initialize coarse alignment are not always available. Recently, local feature-based SIFT-like matching proves competent to handle all such variations without registration. In this paper, towards 3D face recognition for real-life biometric applications, we significantly extend the SIFT-like matching framework to mesh data and propose a novel approach using fine-grained matching of 3D keypoint descriptors. First, two principal curvature-based 3D keypoint detectors are provided, which can repeatedly identify complementary locations on a face scan where local curvatures are high. Then, a robust 3D local coordinate system is built at each keypoint, which allows extraction of pose-invariant features. Three keypoint descriptors, corresponding to three surface differential quantities, are designed, and their feature-level fusion is employed to comprehensively describe local shapes of detected keypoints. Finally, we propose a multi-task sparse representation based fine-grained matching algorithm, which accounts for the average reconstruction error of probe face descriptors sparsely represented by a large dictionary of gallery descriptors in identification. Our approach is evaluated on the Bosphorus database and achieves rank-one recognition rates of 96.56, 98.82, 91.14, and 99.21 % on the entire database, and the expression, pose, and occlusion subsets, respectively. To the best of our knowledge, these are the best results reported so far on this database. Additionally, good generalization ability is also exhibited by the experiments on the FRGC v2.0 database.

Ear wax

Science.gov (United States)

See your provider if your ears are blocked with wax and you are unable to remove the wax. Also call if you have an ear wax blockage and you develop new symptoms, such as: Drainage from the ear Ear pain Fever Hearing loss that continues after you clean the wax

Position-Invariant Robust Features for Long-Term Recognition of Dynamic Outdoor Scenes

Science.gov (United States)

Kawewong, Aram; Tangruamsub, Sirinart; Hasegawa, Osamu

A novel Position-Invariant Robust Feature, designated as PIRF, is presented to address the problem of highly dynamic scene recognition. The PIRF is obtained by identifying existing local features (i.e. SIFT) that have a wide baseline visibility within a place (one place contains more than one sequential images). These wide-baseline visible features are then represented as a single PIRF, which is computed as an average of all descriptors associated with the PIRF. Particularly, PIRFs are robust against highly dynamical changes in scene: a single PIRF can be matched correctly against many features from many dynamical images. This paper also describes an approach to using these features for scene recognition. Recognition proceeds by matching an individual PIRF to a set of features from test images, with subsequent majority voting to identify a place with the highest matched PIRF. The PIRF system is trained and tested on 2000+ outdoor omnidirectional images and on COLD datasets. Despite its simplicity, PIRF offers a markedly better rate of recognition for dynamic outdoor scenes (ca. 90%) than the use of other features. Additionally, a robot navigation system based on PIRF (PIRF-Nav) can outperform other incremental topological mapping methods in terms of time (70% less) and memory. The number of PIRFs can be reduced further to reduce the time while retaining high accuracy, which makes it suitable for long-term recognition and localization.

PhyloSift: phylogenetic analysis of genomes and metagenomes.

Science.gov (United States)

Darling, Aaron E; Jospin, Guillaume; Lowe, Eric; Matsen, Frederick A; Bik, Holly M; Eisen, Jonathan A

2014-01-01

Like all organisms on the planet, environmental microbes are subject to the forces of molecular evolution. Metagenomic sequencing provides a means to access the DNA sequence of uncultured microbes. By combining DNA sequencing of microbial communities with evolutionary modeling and phylogenetic analysis we might obtain new insights into microbiology and also provide a basis for practical tools such as forensic pathogen detection. In this work we present an approach to leverage phylogenetic analysis of metagenomic sequence data to conduct several types of analysis. First, we present a method to conduct phylogeny-driven Bayesian hypothesis tests for the presence of an organism in a sample. Second, we present a means to compare community structure across a collection of many samples and develop direct associations between the abundance of certain organisms and sample metadata. Third, we apply new tools to analyze the phylogenetic diversity of microbial communities and again demonstrate how this can be associated to sample metadata. These analyses are implemented in an open source software pipeline called PhyloSift. As a pipeline, PhyloSift incorporates several other programs including LAST, HMMER, and pplacer to automate phylogenetic analysis of protein coding and RNA sequences in metagenomic datasets generated by modern sequencing platforms (e.g., Illumina, 454).

PhyloSift: phylogenetic analysis of genomes and metagenomes

Directory of Open Access Journals (Sweden)

Aaron E. Darling

2014-01-01

Full Text Available Like all organisms on the planet, environmental microbes are subject to the forces of molecular evolution. Metagenomic sequencing provides a means to access the DNA sequence of uncultured microbes. By combining DNA sequencing of microbial communities with evolutionary modeling and phylogenetic analysis we might obtain new insights into microbiology and also provide a basis for practical tools such as forensic pathogen detection.In this work we present an approach to leverage phylogenetic analysis of metagenomic sequence data to conduct several types of analysis. First, we present a method to conduct phylogeny-driven Bayesian hypothesis tests for the presence of an organism in a sample. Second, we present a means to compare community structure across a collection of many samples and develop direct associations between the abundance of certain organisms and sample metadata. Third, we apply new tools to analyze the phylogenetic diversity of microbial communities and again demonstrate how this can be associated to sample metadata.These analyses are implemented in an open source software pipeline called PhyloSift. As a pipeline, PhyloSift incorporates several other programs including LAST, HMMER, and pplacer to automate phylogenetic analysis of protein coding and RNA sequences in metagenomic datasets generated by modern sequencing platforms (e.g., Illumina, 454.

Ear Pieces

Science.gov (United States)

DiJulio, Betsy

2011-01-01

In this article, the author describes an art project wherein students make fanciful connections between art and medicine. This project challenges students to interpret "ear idioms" (e.g. "blow it out your ear," "in one ear and out the other") by relying almost entirely on realistic ear drawings, the placement of them, marks, and values. In that…

Advances in On-line Absolute Trace Gas Analysis by SIFT-MS

Czech Academy of Sciences Publication Activity Database

Španěl, Patrik; Smith, D.

2013-01-01

Roč. 9, č. 4 (2013), s. 525-539 ISSN 1573-4110 Institutional support: RVO:61388955 Keywords : selected ion flow tube mass spectrometry * SIFT-MS * volatile organic compounds Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.194, year: 2013

PROGRESS IN SIFT-MS: BREATH ANALYSIS AND OTHER APPLICATIONS

Czech Academy of Sciences Publication Activity Database

Španěl, Patrik; Smith, D.

2011-01-01

Roč. 30, č. 2 (2011), s. 236-267 ISSN 0277-7037 R&D Projects: GA MPO FT-TA4/124; GA ČR GA202/09/0800; GA ČR GA203/09/0256 Institutional research plan: CEZ:AV0Z40400503 Keywords : SIFT-MS * breath analysis * ion flow tube Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 10.461, year: 2011

Exemplar Based Recognition of Visual Shapes

DEFF Research Database (Denmark)

Olsen, Søren I.

2005-01-01

This paper presents an approach of visual shape recognition based on exemplars of attributed keypoints. Training is performed by storing exemplars of keypoints detected in labeled training images. Recognition is made by keypoint matching and voting according to the labels for the matched keypoint....... The matching is insensitive to rotations, limited scalings and small deformations. The recognition is robust to noise, background clutter and partial occlusion. Recognition is possible from few training images and improve with the number of training images.......This paper presents an approach of visual shape recognition based on exemplars of attributed keypoints. Training is performed by storing exemplars of keypoints detected in labeled training images. Recognition is made by keypoint matching and voting according to the labels for the matched keypoints...

Fascioperichondrial Flap with a Proximal Base Combined with Prominent Ear Surgery

Directory of Open Access Journals (Sweden)

Heval Selman Özkan

2017-08-01

Full Text Available Objective: In this article, we present a personalized surgical technique to relocate a fascioperichondrial flap with a proximal base as an additional measure to improve results and hide sharp edges which frequently occur following traditional otoplasty. Materials and Methods: Fascioperichondrial flap with a proximal base prepared from the dorsal side was transposed to the anterior helix and conchal excision side and secured with stitches to hide visible edges and reinforce Furnas sutures. Nine patients operated for prominent ear deformity using this modification were included in the study and follow-up period was at least 6 months. Conchal mastoid distances were calculated from the superior and middle third of the ears before and after the operation, also in follow-up controls to determine the efficiency of the method. Results: There were no suture extrusions, skin necrosis or infection. The mean difference for both the upper and middle third of the ears were considerably lower (p≤0.05 at the end of six month after the operation. There were no visible skin edges and discomfort described by the patients. Conclusion: Fascioperichondrial flap with a proximal base repositioning to conchal side is an easy procedure that can be applied simply as an adjunct to traditional techniques. Addition of this flap provides an additional tissue to reinforce suture repair and, the results seem to be more durable and strong. Another main advantage of this flap is eliminating the unnatural visible breakpoints in the conchal bowl.

Object Attention Patches for Text Detection and Recognition in Scene Images using SIFT

NARCIS (Netherlands)

Sriman, Bowornrat; Schomaker, Lambertus; De Marsico, Maria; Figueiredo, Mário; Fred, Ana

2015-01-01

Natural urban scene images contain many problems for character recognition such as luminance noise, varying font styles or cluttered backgrounds. Detecting and recognizing text in a natural scene is a difficult problem. Several techniques have been proposed to overcome these problems. These are,

"COCHLEAR IMPLANTATION IN PATIENTS WITH INNER EAR MALFORMATIONS"

Directory of Open Access Journals (Sweden)

P. Borghei S. Abdi

2004-08-01

Full Text Available Performing cochlear implantation in patients with inner ear malformation has always been a matter of dispute. This study was designed to analyze the operative findings,complications, and postoperative performance of patients with inner ear anomalies who underwent cochlear implantation. Six patients with inner ear malformations underwent implantation in our academic tertiary referral center from 1997 to 2002. The average follow-up period was 27 months. Malformations included one incomplete partition, one common cavity, one narrow internal acoustic canal (IAC in a patient with Riley-Day syndrome and 3 cases of large vestibular aqueduct. All received multi-channel implants either Nucleus 22 or Clarion device. Facial nerve was anomalous in 2 cases. CSF gusher occurred in 4 patients, which was controlled with packing the cochleostomy site. In all cases, the full length of electrode array was inserted, except one with Mondini's dysplasia where insertion failed in the first operation and was referred to another center for a successful surgery on the opposite ear. No other surgical complications were encountered. In 4 cases, all the 22 electrodes could be activated. All patients showed improved hearing performance after implantation. Four showed open-set speech recognition. The one with narrow IAC showed improved awareness to environmental sounds. In the other case (common cavity, the perception tests could not be performed because of very young age. Cochlear implantation in patients with inner ear malformations is a successful way of rehabilitation, although complications should be expected and auditory responses may be highly variable and relatively moderate.

Improving scale invariant feature transform-based descriptors with shape-color alliance robust feature

Science.gov (United States)

Wang, Rui; Zhu, Zhengdan; Zhang, Liang

2015-05-01

Constructing appropriate descriptors for interest points in image matching is a critical aspect task in computer vision and pattern recognition. A method as an extension of the scale invariant feature transform (SIFT) descriptor called shape-color alliance robust feature (SCARF) descriptor is presented. To address the problem that SIFT is designed mainly for gray images and lack of global information for feature points, the proposed approach improves the SIFT descriptor by means of a concentric-rings model, as well as integrating the color invariant space and shape context with SIFT to construct the SCARF descriptor. The SCARF method developed is more robust than the conventional SIFT with respect to not only the color and photometrical variations but also the measuring similarity as a global variation between two shapes. A comparative evaluation of different descriptors is carried out showing that the SCARF approach provides better results than the other four state-of-the-art related methods.

End-Stop Exemplar Based Recognition

DEFF Research Database (Denmark)

Olsen, Søren I.

2003-01-01

An approach to exemplar based recognition of visual shapes is presented. The shape information is described by attributed interest points (keys) detected by an end-stop operator. The attributes describe the statistics of lines and edges local to the interest point, the position of neighboring int...... interest points, and (in the training phase) a list of recognition names. Recognition is made by a simple voting procedure. Preliminary experiments indicate that the recognition is robust to noise, small deformations, background clutter and partial occlusion....

Scene recognition and colorization for vehicle infrared images

Science.gov (United States)

Hou, Junjie; Sun, Shaoyuan; Shen, Zhenyi; Huang, Zhen; Zhao, Haitao

2016-10-01

In order to make better use of infrared technology for driving assistance system, a scene recognition and colorization method is proposed in this paper. Various objects in a queried infrared image are detected and labelled with proper categories by a combination of SIFT-Flow and MRF model. The queried image is then colorized by assigning corresponding colors according to the categories of the objects appeared. The results show that the strategy here emphasizes important information of the IR images for human vision and could be used to broaden the application of IR images for vehicle driving.

Cosmetic ear surgery

Science.gov (United States)

Otoplasty; Ear pinning; Ear surgery - cosmetic; Ear reshaping; Pinnaplasty ... Cosmetic ear surgery may be done in the surgeon's office, an outpatient clinic, or a hospital. It can be performed under ...

Swimmer's Ear

Science.gov (United States)

... Eardrum Taking Care of Your Ears Can Loud Music Hurt My Ears? Your Ears What's Earwax? How Do Pain Relievers Work? View more About Us Contact Us Partners Editorial Policy Permissions Guidelines Privacy Policy & Terms of Use Notice ...

A Room-Temperature Pre-calibration Procedure for Gradiometer Sifting

International Nuclear Information System (INIS)

Zhang Shu-Lin; Liu Yang-Bo; Wang Yong-Liang; Kong Xiang-Yan; Xie Xiao-Ming; Liu Ming

2011-01-01

In order to detect extremely weak magnetic signals, superconducting quantum interference device (SQUID) gradiometers are widely used to suppress environmental noise. A hardware SQUID gradiometer consists of a niobium gradio-antenna and an SQUID, which are coupled via an input coil. Here gradiometer imbalance may greatly reduce its noise suppression performance. The gradiometer balance depends on the geometrical forms of the antenna wound by niobium wire. We describe a simple method based on Faraday's law for the pre-calibration of the gradiometer balance at room temperature, before the gradiometer is set up. The pre-calibrating results are compared with the measured balance of an SQUID gradiometer system. This method may be used for sifting hardware gradiometers for multi-channel systems. (cross-disciplinary physics and related areas of science and technology)

Localisation of the brain in fetal MRI using bundled SIFT features.

Science.gov (United States)

Keraudren, Kevin; Kyriakopoulou, Vanessa; Rutherford, Mary; Hajnal, Joseph V; Rueckert, Daniel

2013-01-01

Fetal MRI is a rapidly emerging diagnostic imaging tool. Its main focus is currently on brain imaging, but there is a huge potential for whole body studies. We propose a method for accurate and robust localisation of the fetal brain in MRI when the image data is acquired as a stack of 2D slices misaligned due to fetal motion. We first detect possible brain locations in 2D images with a Bag-of-Words model using SIFT features aggregated within Maximally Stable Extremal Regions (called bundled SIFT), followed by a robust fitting of an axis-aligned 3D box to the selected regions. We rely on prior knowledge of the fetal brain development to define size and shape constraints. In a cross-validation experiment, we obtained a median error distance of 5.7mm from the ground truth and no missed detection on a database of 59 fetuses. This 2D approach thus allows a robust detection even in the presence of substantial fetal motion.

A Machine for Pulverizing and Sifting Gari Mash | Odigboh | Nigerian ...

African Journals Online (AJOL)

A prototype machine for pulverizing and sifting gari mash, designed as a companion to the gari frying machine developed by the authors, was built and tested. Driven by an electric motor, the prototype accepts lump3 of dewatered gari mash cuts them up into small pieces by a cake breaker and delivers the pieces by a belt ...

Ear Tubes

Science.gov (United States)

... of the ear drum or eustachian tube, Down Syndrome, cleft palate, and barotrauma (injury to the middle ear caused by a reduction of air pressure, ... specialist) may be warranted if you or your child has experienced repeated ... fluid in the middle ear, barotrauma, or have an anatomic abnormality that ...

In-the-Ear Hearing-Instrument Antenna for ISM-Band Body-Centric Ear-to-Ear Communications

DEFF Research Database (Denmark)

Yatman, William H.; Larsen, Lauge K; Kvist, Søren Helstrup

2012-01-01

A compact 2.45 GHz slot-loop antenna is implemented for the use in the outer shell of an in-the-ear (ITE) hearing instrument (HI). The antenna is optimized for high ear-to-ear path gain (jS21j). The antenna simulation results are presented for two identical antennas, one placed in the center of e...

Dietary Assessment on a Mobile Phone Using Image Processing and Pattern Recognition Techniques: Algorithm Design and System Prototyping

Directory of Open Access Journals (Sweden)

Yasmine Probst

2015-07-01

Full Text Available Dietary assessment, while traditionally based on pen-and-paper, is rapidly moving towards automatic approaches. This study describes an Australian automatic food record method and its prototype for dietary assessment via the use of a mobile phone and techniques of image processing and pattern recognition. Common visual features including scale invariant feature transformation (SIFT, local binary patterns (LBP, and colour are used for describing food images. The popular bag-of-words (BoW model is employed for recognizing the images taken by a mobile phone for dietary assessment. Technical details are provided together with discussions on the issues and future work.

Microbiomes of the normal middle ear and ears with chronic otitis media.

Science.gov (United States)

Minami, Shujiro B; Mutai, Hideki; Suzuki, Tomoko; Horii, Arata; Oishi, Naoki; Wasano, Koichiro; Katsura, Motoyasu; Tanaka, Fujinobu; Takiguchi, Tetsuya; Fujii, Masato; Kaga, Kimitaka

2017-10-01

The aim of this study was to profile and compare the middle ear microbiomes of human subjects with and without chronic otitis media. Prospective multicenter cohort study. All consecutive patients undergoing tympanoplasty surgery for chronic otitis media or ear surgery for conditions other than otitis media were recruited. Sterile swab samples were collected from the middle ear mucosa during surgery. The variable region 4 of the 16S rRNA gene in each sample were amplified using region-specific primers adapted for the Illumina MiSeq sequencer (Illumina, CA, USA)). The sequences were subjected to local blast and classified using Metagenome@KIN (World Fusion, Tokyo, Japan). In total, 155 participants were recruited from seven medical centers. Of these, 88 and 67 had chronic otitis media and normal middle ears, respectively. The most abundant bacterial phyla on the mucosal surfaces of the normal middle ears were Proteobacteria, followed by Actinobacteria, Firmicutes, and Bacteroidetes. The children and adults with normal middle ears differed significantly in terms of middle ear microbiomes. Subjects with chronic otitis media without active inflammation (dry ear) had similar middle ear microbiomes as the normal middle ears group. Subjects with chronic otitis media with active inflammation (wet ear) had a lower prevalence of Proteobacteria and a higher prevalence of Firmicutes than the normal middle ears. The human middle ear is inhabited by more diverse microbial communities than was previously thought. Alteration of the middle ear microbiome may contribute to the pathogenesis of chronic otitis media with active inflammation. 2b. Laryngoscope, 127:E371-E377, 2017. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

MEMS capacitive accelerometer-based middle ear microphone.

Science.gov (United States)

Young, Darrin J; Zurcher, Mark A; Semaan, Maroun; Megerian, Cliff A; Ko, Wen H

2012-12-01

The design, implementation, and characterization of a microelectromechanical systems (MEMS) capacitive accelerometer-based middle ear microphone are presented in this paper. The microphone is intended for middle ear hearing aids as well as future fully implantable cochlear prosthesis. Human temporal bones acoustic response characterization results are used to derive the accelerometer design requirements. The prototype accelerometer is fabricated in a commercial silicon-on-insulator (SOI) MEMS process. The sensor occupies a sensing area of 1 mm × 1 mm with a chip area of 2 mm × 2.4 mm and is interfaced with a custom-designed low-noise electronic IC chip over a flexible substrate. The packaged sensor unit occupies an area of 2.5 mm × 6.2 mm with a weight of 25 mg. The sensor unit attached to umbo can detect a sound pressure level (SPL) of 60 dB at 500 Hz, 35 dB at 2 kHz, and 57 dB at 8 kHz. An improved sound detection limit of 34-dB SPL at 150 Hz and 24-dB SPL at 500 Hz can be expected by employing start-of-the-art MEMS fabrication technology, which results in an articulation index of approximately 0.76. Further micro/nanofabrication technology advancement is needed to enhance the microphone sensitivity for improved understanding of normal conversational speech.

Case-Based Policy and Goal Recognition

Science.gov (United States)

2015-09-30

Policy and Goal Recognizer (PaGR), a case- based system for multiagent keyhole recognition. PaGR is a knowledge recognition component within a decision...However, unlike our agent in the BVR domain, these recognition agents have access to perfect information. Single-agent keyhole plan recognition can be...listed below: 1. Facing Target 2. Closing on Target 3. Target Range 4. Within a Target’s Weapon Range 5. Has Target within Weapon Range 6. Is in Danger

The Relationship between Binaural Benefit and Difference in Unilateral Speech Recognition Performance for Bilateral Cochlear Implant Users

Science.gov (United States)

Yoon, Yang-soo; Li, Yongxin; Kang, Hou-Yong; Fu, Qian-Jie

2011-01-01

Objective The full benefit of bilateral cochlear implants may depend on the unilateral performance with each device, the speech materials, processing ability of the user, and/or the listening environment. In this study, bilateral and unilateral speech performances were evaluated in terms of recognition of phonemes and sentences presented in quiet or in noise. Design Speech recognition was measured for unilateral left, unilateral right, and bilateral listening conditions; speech and noise were presented at 0° azimuth. The “binaural benefit” was defined as the difference between bilateral performance and unilateral performance with the better ear. Study Sample 9 adults with bilateral cochlear implants participated. Results On average, results showed a greater binaural benefit in noise than in quiet for all speech tests. More importantly, the binaural benefit was greater when unilateral performance was similar across ears. As the difference in unilateral performance between ears increased, the binaural advantage decreased; this functional relationship was observed across the different speech materials and noise levels even though there was substantial intra- and inter-subject variability. Conclusions The results indicate that subjects who show symmetry in speech recognition performance between implanted ears in general show a large binaural benefit. PMID:21696329

Color-SIFT model: a robust and an accurate shot boundary detection algorithm

Science.gov (United States)

Sharmila Kumari, M.; Shekar, B. H.

2010-02-01

In this paper, a new technique called color-SIFT model is devised for shot boundary detection. Unlike scale invariant feature transform model that uses only grayscale information and misses important visual information regarding color, here we have adopted different color planes to extract keypoints which are subsequently used to detect shot boundaries. The basic SIFT model has four stages namely scale-space peak selection, keypoint localization, orientation assignment and keypoint descriptor and all these four stages were employed to extract key descriptors in each color plane. The proposed model works on three different color planes and a fusion has been made to take a decision on number of keypoint matches for shot boundary identification and hence is different from the color global scale invariant feature transform that works on quantized images. In addition, the proposed algorithm possess invariance to linear transformation and robust to occlusion and noisy environment. Experiments have been conducted on the standard TRECVID video database to reveal the performance of the proposed model.

Ambient analysis of trace compounds in gaseous media by SIFT-MS

Czech Academy of Sciences Publication Activity Database

Smith, D.; Španěl, Patrik

2011-01-01

Roč. 136, č. 10 (2011), s. 2009-2032 ISSN 0003-2654 R&D Projects: GA ČR GA202/09/0800; GA ČR GA203/09/0256 Institutional research plan: CEZ:AV0Z40400503 Keywords : ion-flow tube * mass spectrometry * SIFT-MS Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 4.230, year: 2011

Superpixel-Based Feature for Aerial Image Scene Recognition

Directory of Open Access Journals (Sweden)

Hongguang Li

2018-01-01

Full Text Available Image scene recognition is a core technology for many aerial remote sensing applications. Different landforms are inputted as different scenes in aerial imaging, and all landform information is regarded as valuable for aerial image scene recognition. However, the conventional features of the Bag-of-Words model are designed using local points or other related information and thus are unable to fully describe landform areas. This limitation cannot be ignored when the aim is to ensure accurate aerial scene recognition. A novel superpixel-based feature is proposed in this study to characterize aerial image scenes. Then, based on the proposed feature, a scene recognition method of the Bag-of-Words model for aerial imaging is designed. The proposed superpixel-based feature that utilizes landform information establishes top-task superpixel extraction of landforms to bottom-task expression of feature vectors. This characterization technique comprises the following steps: simple linear iterative clustering based superpixel segmentation, adaptive filter bank construction, Lie group-based feature quantification, and visual saliency model-based feature weighting. Experiments of image scene recognition are carried out using real image data captured by an unmanned aerial vehicle (UAV. The recognition accuracy of the proposed superpixel-based feature is 95.1%, which is higher than those of scene recognition algorithms based on other local features.

Intra- and intersubject comparison of cochlear implant systems using the Esprit and the Tempo+ behind-the-ear speech processor.

Science.gov (United States)

Kompis, Martin; Jenk, Martin; Vischer, Mattheus W; Seifert, Eberhard; Häusler, Rudolf

2002-12-01

A patient with bilateral profound deafness was implanted with a Nucleus CI24M cochlear implant (CI) and used an Esprit behind-the-ear (BTE) speech processor. Thirteen months later, the implant had to be removed because of a cholesteatoma. As the same electrode could not be reinserted, a Medel combi40s CI was implanted in the same ear, and the patient used a Tempo+ BTE processor. After 1 year of use of the Combi40s/Tempo+ system, speech recognition was better and was rated better subjectively than with the CI24M/Esprit system. Speech recognition and subjective ratings were also assessed for two matched groups of nine CI users each, using either an Esprit or a Tempo+ processor. On average, speech recognition scores were higher for the group of Tempo+ users, but the difference was not statistically significant. Users of the Esprit processors rated their device higher in terms of cosmetic appearance and comfort of wearing.

Random-Profiles-Based 3D Face Recognition System

Directory of Open Access Journals (Sweden)

Joongrock Kim

2014-03-01

Full Text Available In this paper, a noble nonintrusive three-dimensional (3D face modeling system for random-profile-based 3D face recognition is presented. Although recent two-dimensional (2D face recognition systems can achieve a reliable recognition rate under certain conditions, their performance is limited by internal and external changes, such as illumination and pose variation. To address these issues, 3D face recognition, which uses 3D face data, has recently received much attention. However, the performance of 3D face recognition highly depends on the precision of acquired 3D face data, while also requiring more computational power and storage capacity than 2D face recognition systems. In this paper, we present a developed nonintrusive 3D face modeling system composed of a stereo vision system and an invisible near-infrared line laser, which can be directly applied to profile-based 3D face recognition. We further propose a novel random-profile-based 3D face recognition method that is memory-efficient and pose-invariant. The experimental results demonstrate that the reconstructed 3D face data consists of more than 50 k 3D point clouds and a reliable recognition rate against pose variation.

Comparing grapheme-based and phoneme-based speech recognition for Afrikaans

CSIR Research Space (South Africa)

Basson, WD

2012-11-01

Full Text Available This paper compares the recognition accuracy of a phoneme-based automatic speech recognition system with that of a grapheme-based system, using Afrikaans as case study. The first system is developed using a conventional pronunciation dictionary...

Play it by Ear

DEFF Research Database (Denmark)

Kammersgaard, Nikolaj Peter Iversen; Kvist, Søren Helstrup; Thaysen, Jesper

2014-01-01

The first antenna for ear-to-ear communication with a standard Bluetooth chip has the potential to improve hearing aid technology.......The first antenna for ear-to-ear communication with a standard Bluetooth chip has the potential to improve hearing aid technology....

(DCT-FY08) Target Detection Using Multiple Modality Airborne and Ground Based Sensors

Science.gov (United States)

2013-03-01

resolution SIFT grids in metric-topological SLAM ,” in Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2009. [4] M. Bosse and R...single camera SLAM ,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 6, pp. 1052–1067, 2007. [7] D. Nister, O. Naroditsky, and J. Bergen...segmentation with ground-based and airborne LIDAR range data,” in Proceedings of the Fourth International Symposium on 3D Data Processing

Securing SIFT: Privacy-preserving Outsourcing Computation of Feature Extractions Over Encrypted Image Data.

Science.gov (United States)

Hu, Shengshan; Wang, Qian; Wang, Jingjun; Qin, Zhan; Ren, Kui

2016-05-13

Advances in cloud computing have greatly motivated data owners to outsource their huge amount of personal multimedia data and/or computationally expensive tasks onto the cloud by leveraging its abundant resources for cost saving and flexibility. Despite the tremendous benefits, the outsourced multimedia data and its originated applications may reveal the data owner's private information, such as the personal identity, locations or even financial profiles. This observation has recently aroused new research interest on privacy-preserving computations over outsourced multimedia data. In this paper, we propose an effective and practical privacy-preserving computation outsourcing protocol for the prevailing scale-invariant feature transform (SIFT) over massive encrypted image data. We first show that previous solutions to this problem have either efficiency/security or practicality issues, and none can well preserve the important characteristics of the original SIFT in terms of distinctiveness and robustness. We then present a new scheme design that achieves efficiency and security requirements simultaneously with the preservation of its key characteristics, by randomly splitting the original image data, designing two novel efficient protocols for secure multiplication and comparison, and carefully distributing the feature extraction computations onto two independent cloud servers. We both carefully analyze and extensively evaluate the security and effectiveness of our design. The results show that our solution is practically secure, outperforms the state-of-theart, and performs comparably to the original SIFT in terms of various characteristics, including rotation invariance, image scale invariance, robust matching across affine distortion, addition of noise and change in 3D viewpoint and illumination.

SecSIFT: Privacy-preserving Outsourcing Computation of Feature Extractions Over Encrypted Image Data.

Science.gov (United States)

Hu, Shengshan; Wang, Qian; Wang, Jingjun; Qin, Zhan; Ren, Kui

2016-05-13

Advances in cloud computing have greatly motivated data owners to outsource their huge amount of personal multimedia data and/or computationally expensive tasks onto the cloud by leveraging its abundant resources for cost saving and flexibility. Despite the tremendous benefits, the outsourced multimedia data and its originated applications may reveal the data owner's private information, such as the personal identity, locations or even financial profiles. This observation has recently aroused new research interest on privacy-preserving computations over outsourced multimedia data. In this paper, we propose an effective and practical privacy-preserving computation outsourcing protocol for the prevailing scale-invariant feature transform (SIFT) over massive encrypted image data. We first show that previous solutions to this problem have either efficiency/security or practicality issues, and none can well preserve the important characteristics of the original SIFT in terms of distinctiveness and robustness. We then present a new scheme design that achieves efficiency and security requirements simultaneously with the preservation of its key characteristics, by randomly splitting the original image data, designing two novel efficient protocols for secure multiplication and comparison, and carefully distributing the feature extraction computations onto two independent cloud servers. We both carefully analyze and extensively evaluate the security and effectiveness of our design. The results show that our solution is practically secure, outperforms the state-of-theart, and performs comparably to the original SIFT in terms of various characteristics, including rotation invariance, image scale invariance, robust matching across affine distortion, addition of noise and change in 3D viewpoint and illumination.

Inner-ear sound pressures near the base of the cochlea in chinchilla: Further investigation

Science.gov (United States)

Ravicz, Michael E.; Rosowski, John J.

2013-01-01

The middle-ear pressure gain GMEP, the ratio of sound pressure in the cochlear vestibule PV to sound pressure at the tympanic membrane PTM, is a descriptor of middle-ear sound transfer and the cochlear input for a given stimulus in the ear canal. GMEP and the cochlear partition differential pressure near the cochlear base ΔPCP, which determines the stimulus for cochlear partition motion and has been linked to hearing ability, were computed from simultaneous measurements of PV, PTM, and the sound pressure in scala tympani near the round window PST in chinchilla. GMEP magnitude was approximately 30 dB between 0.1 and 10 kHz and decreased sharply above 20 kHz, which is not consistent with an ideal transformer or a lossless transmission line. The GMEP phase was consistent with a roughly 50-μs delay between PV and PTM. GMEP was little affected by the inner-ear modifications necessary to measure PST. GMEP is a good predictor of ΔPCP at low and moderate frequencies where PV ⪢ PST but overestimates ΔPCP above a few kilohertz where PV ≈ PST. The ratio of PST to PV provides insight into the distribution of sound pressure within the cochlear scalae. PMID:23556590

Haar-like Rectangular Features for Biometric Recognition

DEFF Research Database (Denmark)

Nasrollahi, Kamal; Moeslund, Thomas B.; Rashidi, Maryam

2013-01-01

Developing a reliable, fast, and robust biometric recognition system is still a challenging task. This is because the inputs to these systems can be noisy, occluded, poorly illuminated, rotated, and of very low-resolutions. This paper proposes a probabilistic classifier using Haar-like features......, which mostly have been used for detection, for biometric recognition. The proposed system has been tested for three different biometrics: ear, iris, and hand vein patterns and it is shown that it is robust against most of the mentioned degradations and it outperforms state-of-the-art systems...

Hairy ears; Revisited

Directory of Open Access Journals (Sweden)

Daifullah Al Aboud

2014-04-01

Full Text Available Hair can grow in areas which are not usually hairy in human skin. The Online Mendelian Inheritance in Man (OMIM (http:// www.ncbi.nlm.nih.gov/omimhave some entries in this regards. These include ( %139600 – HAIRY ELBOWS, #605130 – HAIRY ELBOWS, SHORT STATURE, FACIAL DYSMORPHISM, AND DEVELOPMENTAL DELAY, 139630 – HAIRY NOSE TIP, 139500 – HAIRY EARS, and 425500 – HAIRY EARS, Y-LINKED. Hairy ears, (Fig. 1, are uncommon trait and it is rare to see a person with very long hair on the ears.

Unvoiced Speech Recognition Using Tissue-Conductive Acoustic Sensor

Directory of Open Access Journals (Sweden)

Heracleous Panikos

2007-01-01

Full Text Available We present the use of stethoscope and silicon NAM (nonaudible murmur microphones in automatic speech recognition. NAM microphones are special acoustic sensors, which are attached behind the talker's ear and can capture not only normal (audible speech, but also very quietly uttered speech (nonaudible murmur. As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech transform, etc. for sound-impaired people. Using adaptation techniques and a small amount of training data, we achieved for a 20 k dictation task a word accuracy for nonaudible murmur recognition in a clean environment. In this paper, we also investigate nonaudible murmur recognition in noisy environments and the effect of the Lombard reflex on nonaudible murmur recognition. We also propose three methods to integrate audible speech and nonaudible murmur recognition using a stethoscope NAM microphone with very promising results.

Regression-based Multi-View Facial Expression Recognition

NARCIS (Netherlands)

Rudovic, Ognjen; Patras, Ioannis; Pantic, Maja

2010-01-01

We present a regression-based scheme for multi-view facial expression recognition based on 2蚠D geometric features. We address the problem by mapping facial points (e.g. mouth corners) from non-frontal to frontal view where further recognition of the expressions can be performed using a

Three dimensional pattern recognition using feature-based indexing and rule-based search

Science.gov (United States)

Lee, Jae-Kyu

In flexible automated manufacturing, robots can perform routine operations as well as recover from atypical events, provided that process-relevant information is available to the robot controller. Real time vision is among the most versatile sensing tools, yet the reliability of machine-based scene interpretation can be questionable. The effort described here is focused on the development of machine-based vision methods to support autonomous nuclear fuel manufacturing operations in hot cells. This thesis presents a method to efficiently recognize 3D objects from 2D images based on feature-based indexing. Object recognition is the identification of correspondences between parts of a current scene and stored views of known objects, using chains of segments or indexing vectors. To create indexed object models, characteristic model image features are extracted during preprocessing. Feature vectors representing model object contours are acquired from several points of view around each object and stored. Recognition is the process of matching stored views with features or patterns detected in a test scene. Two sets of algorithms were developed, one for preprocessing and indexed database creation, and one for pattern searching and matching during recognition. At recognition time, those indexing vectors with the highest match probability are retrieved from the model image database, using a nearest neighbor search algorithm. The nearest neighbor search predicts the best possible match candidates. Extended searches are guided by a search strategy that employs knowledge-base (KB) selection criteria. The knowledge-based system simplifies the recognition process and minimizes the number of iterations and memory usage. Novel contributions include the use of a feature-based indexing data structure together with a knowledge base. Both components improve the efficiency of the recognition process by improved structuring of the database of object features and reducing data base size

In-the-wild facial expression recognition in extreme poses

Science.gov (United States)

Yang, Fei; Zhang, Qian; Zheng, Chi; Qiu, Guoping

2018-04-01

In the computer research area, facial expression recognition is a hot research problem. Recent years, the research has moved from the lab environment to in-the-wild circumstances. It is challenging, especially under extreme poses. But current expression detection systems are trying to avoid the pose effects and gain the general applicable ability. In this work, we solve the problem in the opposite approach. We consider the head poses and detect the expressions within special head poses. Our work includes two parts: detect the head pose and group it into one pre-defined head pose class; do facial expression recognize within each pose class. Our experiments show that the recognition results with pose class grouping are much better than that of direct recognition without considering poses. We combine the hand-crafted features, SIFT, LBP and geometric feature, with deep learning feature as the representation of the expressions. The handcrafted features are added into the deep learning framework along with the high level deep learning features. As a comparison, we implement SVM and random forest to as the prediction models. To train and test our methodology, we labeled the face dataset with 6 basic expressions.

Individual recognition based on communication behaviour of male fowl.

Science.gov (United States)

Smith, Carolynn L; Taubert, Jessica; Weldon, Kimberly; Evans, Christopher S

2016-04-01

Correctly directing social behaviour towards a specific individual requires an ability to discriminate between conspecifics. The mechanisms of individual recognition include phenotype matching and familiarity-based recognition. Communication-based recognition is a subset of familiarity-based recognition wherein the classification is based on behavioural or distinctive signalling properties. Male fowl (Gallus gallus) produce a visual display (tidbitting) upon finding food in the presence of a female. Females typically approach displaying males. However, males may tidbit without food. We used the distinctiveness of the visual display and the unreliability of some males to test for communication-based recognition in female fowl. We manipulated the prior experience of the hens with the males to create two classes of males: S(+) wherein the tidbitting signal was paired with a food reward to the female, and S (-) wherein the tidbitting signal occurred without food reward. We then conducted a sequential discrimination test with hens using a live video feed of a familiar male. The results of the discrimination tests revealed that hens discriminated between categories of males based on their signalling behaviour. These results suggest that fowl possess a communication-based recognition system. This is the first demonstration of live-to-video transfer of recognition in any species of bird. Copyright © 2016 Elsevier B.V. All rights reserved.

Computed Tomography Findings of a Patient With Severe Dysplasia of the Inner Ear and Recurrent Meningitis: A Case Report of Gusher Ear in a Five-Year Old Boy

International Nuclear Information System (INIS)

Alizadeh, Houman; Nasri, Fatemeh; Mehdizadeh, Mehrzad; Jamsa, Shahin

2014-01-01

Communication between subarachnoid and perlymphatic spaces can be due to a deficiency of lamina cribrosa (stapes gusher). Recognition of the condition may alter the course of treatment that can avoid perilymph gushing. A five-year-old boy presented with a history of congenital hearing loss and recurrent meningitis. The computed tomography (CT) of the temporal bone showed severe bilateral dysplasia in the inner ears in favor of gusher disease

Mass spectrometric studies of bimolecular reactions in a selected ion flow tube (SIFT)

International Nuclear Information System (INIS)

Shul, R.J.; Upschulte, B.L.; Passarella, R.; Keesee, R.G.; Castleman, A.W.

1985-01-01

The rate coefficients for a number of thermal energy charge transfer reactions have been obtained with a selected ion flow tube (SIFT). The reactions studied involve Ar + and Ar 2 + with a variety of neutral molecules including: O 2 , CS 2 , CO 2 , SO 2 , H 2 S, NH 3 , and SF 6 . Such reactions have been of long-standing interest in the field of gas-phase ion-molecule chemistry from both a practical and fundamental point of view. Consideration of charge transfer reactions as possible sources of chemical lasers and their role in ionospheric and interstellar chemistry account for much of the interest. Fundamentally, the mechanism involved in these reactions has yet to be definitively established. The consumption deposition of energy into internal modes and translational degrees of freedom in such reactions has also been a topic of considerable debate. The apparatus consists of five main components: an ion source, SIFT quadrupole, ion injector, flow tube, and a mass spectrometer detection system. Ions formed in a high pressure source leak into a SIFT quadrupole where they are mass selected. The primary ion of interest is then injected into the flow tube where reactions are studied. Once in the flow tube the ions are carried downstream by an inert buffer gas, either argon, nitrogen, or helium in the present study. Neutral reactant gas is added through a reactant gas inlet (RGI) at an appropriate location downstream in the flow tube, and allowed to react with the injected ions. Ions on the flow tube axis are sampled through a 1 mm orifice where they are mass analyzed by a second quadrupole mass spectrometer and detected with a channeltron electron multiplier

Selected ion flow tube, SIFT, studies of the reactions of H3O+, NO+ and O2 + with some biologically active isobaric compounds in preparation for SIFT-MS analyses

Czech Academy of Sciences Publication Activity Database

Smith, D.; Chippendale, T. W. E.; Španěl, Patrik

2011-01-01

Roč. 303, 2-3 (2011), s. 81-89 ISSN 1387-3806 R&D Projects: GA ČR GA202/09/0800; GA ČR GA203/09/0256 Institutional research plan: CEZ:AV0Z40400503 Keywords : SIFT-MS * ion-molecule reactions * proton transfers Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.549, year: 2011

Features fusion based approach for handwritten Gujarati character recognition

Directory of Open Access Journals (Sweden)

Ankit Sharma

2017-02-01

Full Text Available Handwritten character recognition is a challenging area of research. Lots of research activities in the area of character recognition are already done for Indian languages such as Hindi, Bangla, Kannada, Tamil and Telugu. Literature review on handwritten character recognition indicates that in comparison with other Indian scripts research activities on Gujarati handwritten character recognition are very less.  This paper aims to bring Gujarati character recognition in attention. Recognition of isolated Gujarati handwritten characters is proposed using three different kinds of features and their fusion. Chain code based, zone based and projection profiles based features are utilized as individual features. One of the significant contribution of proposed work is towards the generation of large and representative dataset of 88,000 handwritten Gujarati characters. Experiments are carried out on this developed dataset. Artificial Neural Network (ANN, Support Vector Machine (SVM and Naive Bayes (NB classifier based methods are implemented for handwritten Gujarati character recognition. Experimental results show substantial enhancement over state-of-the-art and authenticate our proposals.

AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITION

Directory of Open Access Journals (Sweden)

K. Meena

2013-11-01

Full Text Available Automatic face recognition remains an interesting but challenging computer vision open problem. Poor illumination is considered as one of the major issue, since illumination changes cause large variation in the facial features. To resolve this, illumination normalization preprocessing techniques are employed in this paper to enhance the face recognition rate. The methods such as Histogram Equalization (HE, Gamma Intensity Correction (GIC, Normalization chain and Modified Homomorphic Filtering (MHF are used for preprocessing. Owing to great success, the texture features are commonly used for face recognition. But these features are severely affected by lighting changes. Hence texture based models Local Binary Pattern (LBP, Local Derivative Pattern (LDP, Local Texture Pattern (LTP and Local Tetra Patterns (LTrPs are experimented under different lighting conditions. In this paper, illumination invariant face recognition technique is developed based on the fusion of illumination preprocessing with local texture descriptors. The performance has been evaluated using YALE B and CMU-PIE databases containing more than 1500 images. The results demonstrate that MHF based normalization gives significant improvement in recognition rate for the face images with large illumination conditions.

Your Ears

Science.gov (United States)

... More on this topic for: Kids Can Loud Music Hurt My Ears? What Is an Ear Infection? Senses Experiment: Model Eardrum Going to the Audiologist What's Earwax? View more About Us Contact Us Partners Editorial Policy Permissions Guidelines Privacy Policy & Terms of Use Notice ...

Identifying position, visibility, dimensions, and angulation of the ear.

Science.gov (United States)

Mohamed, Kasim; Christian, Jayanth; Jeyapalan, Karthigeyan; Natarajan, Shanmuganathan; Banu, Fathima; Veeravalli, Padmanabhan T

2014-01-01

We selected 254 subjects between the ages of 18 and 30 yr to assess the ear position, angulations of the ear in relation to the nose, visibility from the frontal view, and dimensions of the ear by using various anthropometric points of the face. Subjects were divided into four groups based on facial form. A reference plane indicator, facial topographical measurements, metal ruler, and digital photography were used. While considering the position of the ear, in all facial forms except square tapering, the most samples showed a tendency for the subaurale being in line with subnasale. Regression analysis showed a tendency to gnathion distance is the most dependent variable with length of the ear kept as a constant predictor, while both interalar distance and exocanthion to endocanthion distance correlate highly significantly to the width of the ear. In all subjects, the visibility of the ear when viewed from the front was an average of 1.5 mm. Regardless of facial form, ear angulation was generally less than nose angulation.

Human ear detection in the thermal infrared spectrum

Science.gov (United States)

Abaza, Ayman; Bourlai, Thirimachos

2012-06-01

In this paper the problem of human ear detection in the thermal infrared (IR) spectrum is studied in order to illustrate the advantages and limitations of the most important steps of ear-based biometrics that can operate in day and night time environments. The main contributions of this work are two-fold: First, a dual-band database is assembled that consists of visible and thermal profile face images. The thermal data was collected using a high definition middle-wave infrared (3-5 microns) camera that is capable of acquiring thermal imprints of human skin. Second, a fully automated, thermal imaging based ear detection method is developed for real-time segmentation of human ears in either day or night time environments. The proposed method is based on Haar features forming a cascaded AdaBoost classifier (our modified version of the original Viola-Jones approach1 that was designed to be applied mainly in visible band images). The main advantage of the proposed method, applied on our profile face image data set collected in the thermal-band, is that it is designed to reduce the learning time required by the original Viola-Jones method from several weeks to several hours. Unlike other approaches reported in the literature, which have been tested but not designed to operate in the thermal band, our method yields a high detection accuracy that reaches ~ 91.5%. Further analysis on our data set yielded that: (a) photometric normalization techniques do not directly improve ear detection performance. However, when using a certain photometric normalization technique (CLAHE) on falsely detected images, the detection rate improved by ~ 4%; (b) the high detection accuracy of our method did not degrade when we lowered down the original spatial resolution of thermal ear images. For example, even after using one third of the original spatial resolution (i.e. ~ 20% of the original computational time) of the thermal profile face images, the high ear detection accuracy of our method

Ear Acupuncture in European Traditional Medicine

Directory of Open Access Journals (Sweden)

Luigi Gori

2007-01-01

Full Text Available Auricular acupuncture is a diagnostic and treatment system based on normalizing the body's dysfunction through stimulation of definite points on the ear. Rudimentary forms of acupuncture which probably arose during the Stone Age have survived in many parts of the world right down to present day. It was used in the ancient Egypt, Rome, Greece and all the Mediterranean area. It is a microacupuncture technique similar to reflexology, and was first described in France in 1950 by Paul Nogier who is considered the Father of modern ear acupuncture. It was speculated that the technique works because groups of pluripotent cells contain information from the whole organism and create regional organization centers representing different parts of the body. Nevertheless stimulation of a reflex point in the ear seems relieve symptoms of distant pathologies. Modern research is confirming the efficacy of ear acupuncture for analgesia and anxiety related disease, while tobacco dependence and other substance abuse still need confirmation. Actually main methodological problems with auricular acupuncture are that exist too many maps with little agreement regarding point location in the ear, and that the correspondence or reflex systems does not correlated with modern knowledge of anatomy and physiology.

Improved RGB-D-T based Face Recognition

DEFF Research Database (Denmark)

Oliu Simon, Marc; Corneanu, Ciprian; Nasrollahi, Kamal

2016-01-01

years. At the same time a multimodal facial recognition is a promising approach. This paper combines the latest successes in both directions by applying deep learning Convolutional Neural Networks (CNN) to the multimodal RGB-D-T based facial recognition problem outperforming previously published results......Reliable facial recognition systems are of crucial importance in various applications from entertainment to security. Thanks to the deep-learning concepts introduced in the field, a significant improvement in the performance of the unimodal facial recognition systems has been observed in the recent...

Recognition-Based Pedagogy: Teacher Candidates' Experience of Deficit

Science.gov (United States)

Parkison, Paul T.; DaoJensen, Thuy

2014-01-01

This study seeks to introduce what we call "recognition-based pedagogy" as a conceptual frame through which teachers and instructors can collaboratively develop educative experiences with students. Recognition-based pedagogy connects the theories of critical pedagogy, identity politics, and the politics of recognition with the educative…

Nonuniform multiview color texture mapping of image sequence and three-dimensional model for faded cultural relics with sift feature points

Science.gov (United States)

Li, Na; Gong, Xingyu; Li, Hongan; Jia, Pengtao

2018-01-01

For faded relics, such as Terracotta Army, the 2D-3D registration between an optical camera and point cloud model is an important part for color texture reconstruction and further applications. This paper proposes a nonuniform multiview color texture mapping for the image sequence and the three-dimensional (3D) model of point cloud collected by Handyscan3D. We first introduce nonuniform multiview calibration, including the explanation of its algorithm principle and the analysis of its advantages. We then establish transformation equations based on sift feature points for the multiview image sequence. At the same time, the selection of nonuniform multiview sift feature points is introduced in detail. Finally, the solving process of the collinear equations based on multiview perspective projection is given with three steps and the flowchart. In the experiment, this method is applied to the color reconstruction of the kneeling figurine, Tangsancai lady, and general figurine. These results demonstrate that the proposed method provides an effective support for the color reconstruction of the faded cultural relics and be able to improve the accuracy of 2D-3D registration between the image sequence and the point cloud model.

Inner ear barriers to nanomedicine-augmented drug delivery and imaging

Directory of Open Access Journals (Sweden)

Jing Zou

2016-12-01

Full Text Available There are several challenges to inner ear drug delivery and imaging due to the existence of tight biological barriers to the target structure and the dense bone surrounding it. Advances in imaging and nanomedicine may provide knowledge for overcoming the existing limitations to both the diagnosis and treatment of inner ear diseases. Novel techniques have improved the efficacy of drug delivery and targeting to the inner ear, as well as the quality and accuracy of imaging this structure. In this review, we will describe the pathways and biological barriers of the inner ear regarding drug delivery, the beneficial applications and limitations of the imaging techniques available for inner ear research, the behavior of engineered nanomaterials in inner ear applications, and future perspectives for nanomedicine-based inner ear imaging.

Finger Vein Recognition Based on Personalized Weight Maps

Science.gov (United States)

Yang, Gongping; Xiao, Rongyang; Yin, Yilong; Yang, Lu

2013-01-01

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs). The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition. PMID:24025556

Finger Vein Recognition Based on Personalized Weight Maps

Directory of Open Access Journals (Sweden)

Lu Yang

2013-09-01

Full Text Available Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs. The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition.

Gait recognition based on integral outline

Science.gov (United States)

Ming, Guan; Fang, Lv

2017-02-01

Biometric identification technology replaces traditional security technology, which has become a trend, and gait recognition also has become a hot spot of research because its feature is difficult to imitate and theft. This paper presents a gait recognition system based on integral outline of human body. The system has three important aspects: the preprocessing of gait image, feature extraction and classification. Finally, using a method of polling to evaluate the performance of the system, and summarizing the problems existing in the gait recognition and the direction of development in the future.

Using Drosophila melanogaster as a model for genotoxic chemical mutational studies with a new program, SnpSift

Directory of Open Access Journals (Sweden)

Douglas Mark Ruden

2012-03-01

Full Text Available This paper describes a new program SnpSift for filtering differential DNA sequence variants between two or more experimental genomes after genotoxic chemical exposure. Here, we illustrate how SnpSift can be used to identify candidate phenotype-relevant variants including single nucleotide polymorphisms (SNPs, multiple nucleotide polymorphisms (MNPs, insertions and deletions (InDels in mutant strains isolated from genome-wide chemical mutagenesis of Drosophila melanogaster. First, the genomes of two independently-isolated mutant fly strains that are allelic for a novel recessive male-sterile locus generated by genotoxic chemical exposure were sequenced using the Illumina next-generation DNA sequencer to obtain 20- to 29-fold coverage of the euchromatic sequences. The sequencing reads were processed and variants were called using standard bioinformatic tools. Next, SnpEff was used to annotate all sequence variants and their potential mutational effects on associated genes. Then, SnpSift was used to filter and select differential variants that potentially disrupt a common gene in the two allelic mutant strains. The potential causative DNA lesions were partially validated by capillary sequencing of PCR-amplified DNA in the genetic interval as defined by meiotic mapping and deletions that remove defined regions of the chromosome. Of the five candidate genes located in the genetic interval, the Pka-like gene CG12069 was found to carry a separate premature stop codon mutation in each of the two allelic mutants whereas the other 4 candidate genes within the interval have wild-type sequences. The Pka-like gene is therefore a strong candidate gene for the male-sterile locus. These results demonstrate that combining SnpEff and SnpSift can expedite the identification of candidate phenotype-causative mutations in chemically-mutagenized Drosophila strains. This technique can also be used to characterize the variety of mutations generated by genotoxic

Taking Care of Your Ears

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... Audiologist Perforated Eardrum What's Hearing Loss? Can Loud Music Hurt My Ears? What Is an Ear Infection? Swimmer's Ear Your Ears What's Earwax? View more About Us Contact Us Partners Editorial Policy Permissions Guidelines Privacy Policy & Terms of Use Notice ...

Artificial Neural Network Based Optical Character Recognition

OpenAIRE

Vivek Shrivastava; Navdeep Sharma

2012-01-01

Optical Character Recognition deals in recognition and classification of characters from an image. For the recognition to be accurate, certain topological and geometrical properties are calculated, based on which a character is classified and recognized. Also, the Human psychology perceives characters by its overall shape and features such as strokes, curves, protrusions, enclosures etc. These properties, also called Features are extracted from the image by means of spatial pixel-...

Direct, rapid quantitative analyses of BVOCs using SIFT-MS and PTR-MS obviating sample collection

Czech Academy of Sciences Publication Activity Database

Smith, D.; Španěl, Patrik

2011-01-01

Roč. 30, č. 7 (2011), s. 945-959 ISSN 0165-9936 Institutional research plan: CEZ:AV0Z40400503 Keywords : SIFT-MS * PTR-MS * Absolute quantification Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 6.273, year: 2011

Unvoiced Speech Recognition Using Tissue-Conductive Acoustic Sensor

Directory of Open Access Journals (Sweden)

Hiroshi Saruwatari

2007-01-01

Full Text Available We present the use of stethoscope and silicon NAM (nonaudible murmur microphones in automatic speech recognition. NAM microphones are special acoustic sensors, which are attached behind the talker's ear and can capture not only normal (audible speech, but also very quietly uttered speech (nonaudible murmur. As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech transform, etc. for sound-impaired people. Using adaptation techniques and a small amount of training data, we achieved for a 20 k dictation task a 93.9% word accuracy for nonaudible murmur recognition in a clean environment. In this paper, we also investigate nonaudible murmur recognition in noisy environments and the effect of the Lombard reflex on nonaudible murmur recognition. We also propose three methods to integrate audible speech and nonaudible murmur recognition using a stethoscope NAM microphone with very promising results.

Stimulus-dependent effects on right ear advantage in schizophrenia

Directory of Open Access Journals (Sweden)

Smucny J

2012-09-01

Full Text Available Jason Smucny,1,3 Korey Wylie,3 Jason Tregellas1–31Neuroscience Program, University of Colorado Anschutz Medical Campus, 2Research Science, Denver VA Medical, Center, 3Department of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, CO, USABackground: When presented with different sounds in each ear (dichotic listening, healthy subjects typically show a preference for stimuli heard in the right ear, an effect termed "right ear advantage". Previous studies examining right ear advantage in schizophrenia have been inconsistent, showing either decreased or increased advantage relative to comparison subjects. Given evidence for enhanced semantic processing in schizophrenia, some of this inconsistency may be due to the type of stimuli presented (words or syllables. The present study examined right ear advantage in patients and controls using both words and syllables as stimuli.Methods: Right ear advantage was compared between 20 patients with schizophrenia and 17 healthy controls. Two versions of the task were used, ie, a consonant-vowel pairing task and a fused rhymed words task.Results: A significant group × task interaction was observed. Relative to healthy controls, patients showed a greater difference on the syllable-based task compared with the word-based task. The number of distractors marked during the syllable-based task was inversely correlated with score on the Global Assessment of Function Scale.Conclusion: The findings are consistent with a left hemisphere dysfunction in schizophrenia, but also suggest that differences may be stimulus-specific, with a relative sparing of the deficit in the context of word stimuli. Performance may be related to measures of social, occupational, and psychological function.Keywords: schizophrenia, right ear advantage, dichotic, distraction

Comparison of active SIFT-based 3D object recognition algorithms

CSIR Research Space (South Africa)

Keaikitse, M

2013-09-01

Full Text Available by the author of [8]. The following is the procedure used for obtaining that dataset. The training and testing datasets were captured using a Prosilica GE1900C camera. Everyday objects such as cereal and spice boxes were used. In compiling the training dataset....88 1 Yes Spice Bottle - - No Spray Can - - No Spray Can2 1.39 1 Yes images satisfies the condition: (|xi − xj | ≤ xT = 12) ∧ (|yi − yj | ≤ yT = 4), In our case, however, the camera is fixed and the object is placed on a rotating turntable. As a result...

A comparative study of image low level feature extraction algorithms

Directory of Open Access Journals (Sweden)

M.M. El-gayar

2013-07-01

Full Text Available Feature extraction and matching is at the base of many computer vision problems, such as object recognition or structure from motion. Current methods for assessing the performance of popular image matching algorithms are presented and rely on costly descriptors for detection and matching. Specifically, the method assesses the type of images under which each of the algorithms reviewed herein perform to its maximum or highest efficiency. The efficiency is measured in terms of the number of matches founds by the algorithm and the number of type I and type II errors encountered when the algorithm is tested against a specific pair of images. Current comparative studies asses the performance of the algorithms based on the results obtained in different criteria such as speed, sensitivity, occlusion, and others. This study addresses the limitations of the existing comparative tools and delivers a generalized criterion to determine beforehand the level of efficiency expected from a matching algorithm given the type of images evaluated. The algorithms and the respective images used within this work are divided into two groups: feature-based and texture-based. And from this broad classification only three of the most widely used algorithms are assessed: color histogram, FAST (Features from Accelerated Segment Test, SIFT (Scale Invariant Feature Transform, PCA-SIFT (Principal Component Analysis-SIFT, F-SIFT (fast-SIFT and SURF (speeded up robust features. The performance of the Fast-SIFT (F-SIFT feature detection methods are compared for scale changes, rotation, blur, illumination changes and affine transformations. All the experiments use repeatability measurement and the number of correct matches for the evaluation measurements. SIFT presents its stability in most situations although its slow. F-SIFT is the fastest one with good performance as the same as SURF, SIFT, PCA-SIFT show its advantages in rotation and illumination changes.

Building and Testing a Statistical Shape Model of the Human Ear Canal

DEFF Research Database (Denmark)

Paulsen, Rasmus Reinhold; Larsen, Rasmus; Laugesen, Søren

2002-01-01

Today the design of custom in-the-ear hearing aids is based on personal experience and skills and not on a systematic description of the variation of the shape of the ear canal. In this paper it is described how a dense surface point distribution model of the human ear canal is built based on a t...

Degraded character recognition based on gradient pattern

Science.gov (United States)

Babu, D. R. Ramesh; Ravishankar, M.; Kumar, Manish; Wadera, Kevin; Raj, Aakash

2010-02-01

Degraded character recognition is a challenging problem in the field of Optical Character Recognition (OCR). The performance of an optical character recognition depends upon printed quality of the input documents. Many OCRs have been designed which correctly identifies the fine printed documents. But, very few reported work has been found on the recognition of the degraded documents. The efficiency of the OCRs system decreases if the input image is degraded. In this paper, a novel approach based on gradient pattern for recognizing degraded printed character is proposed. The approach makes use of gradient pattern of an individual character for recognition. Experiments were conducted on character image that is either digitally written or a degraded character extracted from historical documents and the results are found to be satisfactory.

Material recognition based on thermal cues: Mechanisms and applications.

Science.gov (United States)

Ho, Hsin-Ni

2018-01-01

Some materials feel colder to the touch than others, and we can use this difference in perceived coldness for material recognition. This review focuses on the mechanisms underlying material recognition based on thermal cues. It provides an overview of the physical, perceptual, and cognitive processes involved in material recognition. It also describes engineering domains in which material recognition based on thermal cues have been applied. This includes haptic interfaces that seek to reproduce the sensations associated with contact in virtual environments and tactile sensors aim for automatic material recognition. The review concludes by considering the contributions of this line of research in both science and engineering.

Prenatal evaluation of the middle ear and diagnosis of middle ear hypoplasia using MRI

Energy Technology Data Exchange (ETDEWEB)

Katorza, Eldad; Nahama-Allouche, Catherine; Ducou le Pointe, Hubert; Garel, Catherine [Hopital d' Enfants Armand-Trousseau, Service de Radiologie, Paris (France); Castaigne, Vanina [Hopital Saint-Antoine, Service de Gynecologie-Obstetrique, Paris (France); Gonzales, Marie; Marlin, Sandrine [Hopital d' Enfants Armand-Trousseau, Service de Genetique et Embryologie medicales, Paris (France); Galliani, Eva [Hopital d' Enfants Armand-Trousseau, Service de Chirurgie maxillo-faciale, Paris (France); Jouannic, Jean-Marie; Rosenblatt, Jonathan [Hopital d' Enfants Armand-Trousseau, Service de Gynecologie-Obstetrique, Centre pluridisciplinaire de diagnostic prenatal, Paris (France)

2011-05-15

Analysis of the middle ear with fetal MRI has not been previously reported. To show the contribution of fetal MRI to middle ear imaging. The tympanic cavity was evaluated in 108 fetal cerebral MRI examinations (facial and/or cerebral malformation excluded) and in two cases, one of Treacher Collins syndrome (case 1) and the other of oculo-auriculo-vertebral (OUV) spectrum (case 2) with middle ear hypoplasia identified by MRI at 27 and 36 weeks' gestation, respectively. In all 108 fetuses (mean gestational age 32.5 weeks), the tympanic cavity and T2 hypointensity related to the ossicles were well visualised on both sides. Case 1 had micro/retrognathia and bilateral external ear deformity and case 2 had retrognathism with a left low-set and deformed ear. MRI made it possible to recognize the marked hypoplasia of the tympanic cavity, which was bilateral in case 1 and unilateral in case 2. Both syndromes are characterized by craniofacial abnormalities including middle ear hypoplasia, which cannot be diagnosed with US. The middle ear cavity can be visualized with fetal MRI. We emphasize the use of this imaging modality in the diagnosis of middle ear hypoplasia. (orig.)

Sheep as a large animal ear model: Middle-ear ossicular velocities and intracochlear sound pressure.

Science.gov (United States)

Péus, Dominik; Dobrev, Ivo; Prochazka, Lukas; Thoele, Konrad; Dalbert, Adrian; Boss, Andreas; Newcomb, Nicolas; Probst, Rudolf; Röösli, Christof; Sim, Jae Hoon; Huber, Alexander; Pfiffner, Flurin

2017-08-01

Animals are frequently used for the development and testing of new hearing devices. Dimensions of the middle ear and cochlea differ significantly between humans and commonly used animals, such as rodents or cats. The sheep cochlea is anatomically more like the human cochlea in size and number of turns. This study investigated the middle-ear ossicular velocities and intracochlear sound pressure (ICSP) in sheep temporal bones, with the aim of characterizing the sheep as an experimental model for implantable hearing devices. Measurements were made on fresh sheep temporal bones. Velocity responses of the middle ear ossicles at the umbo, long process of the incus and stapes footplate were measured in the frequency range of 0.25-8 kHz using a laser Doppler vibrometer system. Results were normalized by the corresponding sound pressure level in the external ear canal (P EC ). Sequentially, ICSPs at the scala vestibuli and tympani were then recorded with custom MEMS-based hydrophones, while presenting identical acoustic stimuli. The sheep middle ear transmitted most effectively around 4.8 kHz, with a maximum stapes velocity of 0.2 mm/s/Pa. At the same frequency, the ICSP measurements in the scala vestibuli and tympani showed the maximum gain relative to the P EC (24 dB and 5 dB, respectively). The greatest pressure difference across the cochlear partition occurred between 4 and 6 kHz. A comparison between the results of this study and human reference data showed middle-ear resonance and best cochlear sensitivity at higher frequencies in sheep. In summary, sheep can be an appropriate large animal model for research and development of implantable hearing devices. Copyright © 2017 Elsevier B.V. All rights reserved.

Man machine interface based on speech recognition

International Nuclear Information System (INIS)

Jorge, Carlos A.F.; Aghina, Mauricio A.C.; Mol, Antonio C.A.; Pereira, Claudio M.N.A.

2007-01-01

This work reports the development of a Man Machine Interface based on speech recognition. The system must recognize spoken commands, and execute the desired tasks, without manual interventions of operators. The range of applications goes from the execution of commands in an industrial plant's control room, to navigation and interaction in virtual environments. Results are reported for isolated word recognition, the isolated words corresponding to the spoken commands. For the pre-processing stage, relevant parameters are extracted from the speech signals, using the cepstral analysis technique, that are used for isolated word recognition, and corresponds to the inputs of an artificial neural network, that performs recognition tasks. (author)

Ear-to-Ear On-Body Channel Fading in the ISM-band for Tangentially-Polarized Antennas

DEFF Research Database (Denmark)

Kvist, Søren Helstrup; Thaysen, Jesper; Jakobsen, Kaj Bjarne

2011-01-01

The ear-to-ear on-body channel fading has been studied in the ISM-band. The ear-to-ear path gain was measured on six persons in an indoor environment for a duration of 200 s. The channel fading has been characterized in terms of empirical cumulative distribution functions (CDF), average fade...

Image preprocessing study on KPCA-based face recognition

Science.gov (United States)

Li, Xuan; Li, Dehua

2015-12-01

Face recognition as an important biometric identification method, with its friendly, natural, convenient advantages, has obtained more and more attention. This paper intends to research a face recognition system including face detection, feature extraction and face recognition, mainly through researching on related theory and the key technology of various preprocessing methods in face detection process, using KPCA method, focuses on the different recognition results in different preprocessing methods. In this paper, we choose YCbCr color space for skin segmentation and choose integral projection for face location. We use erosion and dilation of the opening and closing operation and illumination compensation method to preprocess face images, and then use the face recognition method based on kernel principal component analysis method for analysis and research, and the experiments were carried out using the typical face database. The algorithms experiment on MATLAB platform. Experimental results show that integration of the kernel method based on PCA algorithm under certain conditions make the extracted features represent the original image information better for using nonlinear feature extraction method, which can obtain higher recognition rate. In the image preprocessing stage, we found that images under various operations may appear different results, so as to obtain different recognition rate in recognition stage. At the same time, in the process of the kernel principal component analysis, the value of the power of the polynomial function can affect the recognition result.

Congenital inner ear malformations without sensorineural hearing loss.

Science.gov (United States)

Yukawa, Kumiko; Horiguchi, Satoshi; Suzuki, Mamoru

2008-03-01

It has been reported that normal hearing is rare in patients with severe inner ear vestibular malformations [Kokai H, Oohashi M, Ishikawa K, Harada K, Hiratsuka H, Ogasawara M et al. Clinical review of inner ear malformation. J Otolaryngol Jpn 2003;106(10):1038-44; Schuknecht HF. Mondini dysplasia. A clinical pathological study. Ann Otol Rhinol Laryngol 1980;89(Suppl. 65):1-23; Jackler RK, Luxford WM, House WF. Congenital malformations of the inner ear: a classification based on embryogenesis. Laryngoscope 1987;97:2-14; Phelps PD. Congenital lesions of the inner ear, demonstrated by tomography. Arch Otolaryngol 1974;100:11-8]. A 37-year-old woman had combined dysplasia of the posterior and lateral semicircular canals (PSCC, LSCC) with normal cochlear development and normal hearing in both ears. She had complained of dizziness for 8 months. High resolution computed tomography (CT) showed hypogenesis of the bony labyrinth in both ears. Bilateral PSCC and LSCC dysplasia and dilatation of the vestibule were detected. Magnetic resonant imaging (MRI) revealed that the deformity of the PSCC was more severe than the LSCC. Although the caloric test of the left ear elicited no nystagmus and there was reduced response in the right ear, the horizontal vestibulo-occular reflex (VOR) was present. Her dizzy sensation disappeared within 3 months without special treatment. The dizziness attack might have been caused by a temporary breakdown of her peripheral vestibular system.

Physiological artifacts in scalp EEG and ear-EEG.

Science.gov (United States)

Kappel, Simon L; Looney, David; Mandic, Danilo P; Kidmose, Preben

2017-08-11

A problem inherent to recording EEG is the interference arising from noise and artifacts. While in a laboratory environment, artifacts and interference can, to a large extent, be avoided or controlled, in real-life scenarios this is a challenge. Ear-EEG is a concept where EEG is acquired from electrodes in the ear. We present a characterization of physiological artifacts generated in a controlled environment for nine subjects. The influence of the artifacts was quantified in terms of the signal-to-noise ratio (SNR) deterioration of the auditory steady-state response. Alpha band modulation was also studied in an open/closed eyes paradigm. Artifacts related to jaw muscle contractions were present all over the scalp and in the ear, with the highest SNR deteriorations in the gamma band. The SNR deterioration for jaw artifacts were in general higher in the ear compared to the scalp. Whereas eye-blinking did not influence the SNR in the ear, it was significant for all groups of scalps electrodes in the delta and theta bands. Eye movements resulted in statistical significant SNR deterioration in both frontal, temporal and ear electrodes. Recordings of alpha band modulation showed increased power and coherence of the EEG for ear and scalp electrodes in the closed-eyes periods. Ear-EEG is a method developed for unobtrusive and discreet recording over long periods of time and in real-life environments. This study investigated the influence of the most important types of physiological artifacts, and demonstrated that spontaneous activity, in terms of alpha band oscillations, could be recorded from the ear-EEG platform. In its present form ear-EEG was more prone to jaw related artifacts and less prone to eye-blinking artifacts compared to state-of-the-art scalp based systems.

Recognition of chemical entities: combining dictionary-based and grammar-based approaches

Science.gov (United States)

2015-01-01

Background The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. Results The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. Conclusions We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named

Recognition of chemical entities: combining dictionary-based and grammar-based approaches.

Science.gov (United States)

Akhondi, Saber A; Hettne, Kristina M; van der Horst, Eelke; van Mulligen, Erik M; Kors, Jan A

2015-01-01

The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named entity recognition, outperforming

Fast Pedestrian Recognition Based on Multisensor Fusion

Directory of Open Access Journals (Sweden)

Hongyu Hu

2012-01-01

Full Text Available A fast pedestrian recognition algorithm based on multisensor fusion is presented in this paper. Firstly, potential pedestrian locations are estimated by laser radar scanning in the world coordinates, and then their corresponding candidate regions in the image are located by camera calibration and the perspective mapping model. For avoiding time consuming in the training and recognition process caused by large numbers of feature vector dimensions, region of interest-based integral histograms of oriented gradients (ROI-IHOG feature extraction method is proposed later. A support vector machine (SVM classifier is trained by a novel pedestrian sample dataset which adapt to the urban road environment for online recognition. Finally, we test the validity of the proposed approach with several video sequences from realistic urban road scenarios. Reliable and timewise performances are shown based on our multisensor fusing method.

Gene therapy for the inner ear: challenges and promises.

Science.gov (United States)

Ryan, Allen F; Dazert, Stefan

2009-01-01

Since the recognition of genes as the discrete units of heritability, and of DNA as their molecular substrate, the utilization of genes for therapeutic purposes has been recognized as a potential means of correcting genetic disorders. The tools of molecular biology, which allow the manipulation of DNA sequence, provided the means to put this concept into practice. However, progress in the implementation of these ideas has been slow. Here we review the history of the idea of gene therapy and the complexity of genetic disorders. We also discuss the requirements for sequence-based therapy to be accomplished for different types of inherited diseases, as well as the methods available for gene manipulation. The challenges that have limited the applications of gene therapy are reviewed, as are ethical concerns. Finally, we discuss the promise of gene therapy to address inherited and acquired disorders of the inner ear. Copyright (c) 2009 S. Karger AG, Basel.

Body lift, drag and power are relatively higher in large-eared than in small-eared bat species.

Science.gov (United States)

Håkansson, Jonas; Jakobsen, Lasse; Hedenström, Anders; Johansson, L Christoffer

2017-10-01

Bats navigate the dark using echolocation. Echolocation is enhanced by external ears, but external ears increase the projected frontal area and reduce the streamlining of the animal. External ears are thus expected to compromise flight efficiency, but research suggests that very large ears may mitigate the cost by producing aerodynamic lift. Here we compare quantitative aerodynamic measures of flight efficiency of two bat species, one large-eared ( Plecotus auritus ) and one small-eared ( Glossophaga soricina ), flying freely in a wind tunnel. We find that the body drag of both species is higher than previously assumed and that the large-eared species has a higher body drag coefficient, but also produces relatively more ear/body lift than the small-eared species, in line with prior studies on model bats. The measured aerodynamic power of P. auritus was higher than predicted from the aerodynamic model, while the small-eared species aligned with predictions. The relatively higher power of the large-eared species results in lower optimal flight speeds and our findings support the notion of a trade-off between the acoustic benefits of large external ears and aerodynamic performance. The result of this trade-off would be the eco-morphological correlation in bat flight, with large-eared bats generally adopting slow-flight feeding strategies. © 2017 The Author(s).

Automated smartphone audiometry: Validation of a word recognition test app.

Science.gov (United States)

Dewyer, Nicholas A; Jiradejvong, Patpong; Henderson Sabes, Jennifer; Limb, Charles J

2018-03-01

Develop and validate an automated smartphone word recognition test. Cross-sectional case-control diagnostic test comparison. An automated word recognition test was developed as an app for a smartphone with earphones. English-speaking adults with recent audiograms and various levels of hearing loss were recruited from an audiology clinic and were administered the smartphone word recognition test. Word recognition scores determined by the smartphone app and the gold standard speech audiometry test performed by an audiologist were compared. Test scores for 37 ears were analyzed. Word recognition scores determined by the smartphone app and audiologist testing were in agreement, with 86% of the data points within a clinically acceptable margin of error and a linear correlation value between test scores of 0.89. The WordRec automated smartphone app accurately determines word recognition scores. 3b. Laryngoscope, 128:707-712, 2018. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

Low-set ears and pinna abnormalities

Science.gov (United States)

Low-set ears; Microtia; "Lop" ear; Pinna abnormalities; Genetic defect - pinna; Congenital defect - pinna ... conditions: Abnormal folds or location of the pinna Low-set ears No opening to the ear canal ...

Pitfalls in the analysis of volatile breath biomarkers: suggested solutions and SIFT-MS quantification of single metabolites

Czech Academy of Sciences Publication Activity Database

Smith, D.; Španěl, Patrik

2015-01-01

Roč. 9, č. 2 (2015), 022001 ISSN 1752-7155 Institutional support: RVO:61388955 Keywords : SIFT-MS * volatile biomarkers * quantifications Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 4.177, year: 2015

Towards NIRS-based hand movement recognition.

Science.gov (United States)

Paleari, Marco; Luciani, Riccardo; Ariano, Paolo

2017-07-01

This work reports on preliminary results about on hand movement recognition with Near InfraRed Spectroscopy (NIRS) and surface ElectroMyoGraphy (sEMG). Either basing on physical contact (touchscreens, data-gloves, etc.), vision techniques (Microsoft Kinect, Sony PlayStation Move, etc.), or other modalities, hand movement recognition is a pervasive function in today environment and it is at the base of many gaming, social, and medical applications. Albeit, in recent years, the use of muscle information extracted by sEMG has spread out from the medical applications to contaminate the consumer world, this technique still falls short when dealing with movements of the hand. We tested NIRS as a technique to get another point of view on the muscle phenomena and proved that, within a specific movements selection, NIRS can be used to recognize movements and return information regarding muscles at different depths. Furthermore, we propose here three different multimodal movement recognition approaches and compare their performances.

Research on Face Recognition Based on Embedded System

Directory of Open Access Journals (Sweden)

Hong Zhao

2013-01-01

Full Text Available Because a number of image feature data to store, complex calculation to execute during the face recognition, therefore the face recognition process was realized only by PCs with high performance. In this paper, the OpenCV facial Haar-like features were used to identify face region; the Principal Component Analysis (PCA was employed in quick extraction of face features and the Euclidean Distance was also adopted in face recognition; as thus, data amount and computational complexity would be reduced effectively in face recognition, and the face recognition could be carried out on embedded platform. Finally, based on Tiny6410 embedded platform, a set of embedded face recognition systems was constructed. The test results showed that the system has stable operation and high recognition rate can be used in portable and mobile identification and authentication.

THE DESIGN OF KNOWLEDGE BASE FOR SURFACE RELATIONS BASED PART RECOGNITION APPROACH

Directory of Open Access Journals (Sweden)

Adem ÇİÇEK

2007-01-01

Full Text Available In this study, a new knowledge base for an expert system used in part recognition algorithm has been designed. Parts are recognized by the computer program by comparing face adjacency relations and attributes belonging to each part represented in the rules in the knowledge base developed with face adjacency relations and attributes generated from STEP file of the part. Besides, rule writing process has been quite simplified by generating the rules represented in the knowledge base with an automatic rule writing module developed within the system. With the knowledge base and automatic rule writing module used in the part recognition system, simple, intermediate and complex parts can be recognized by a part recognition program.

A miniaturized laser-Doppler-system in the ear canal

Science.gov (United States)

Schmidt, T.; Gerhardt, U.; Kupper, C.; Manske, E.; Witte, H.

2013-03-01

Gathering vibrational data from the human middle ear is quite difficult. To this date the well-known acoustic probe is used to estimate audiometric parameters, e.g. otoacoustic emissions, wideband reflectance and the measurement of the stapedius reflex. An acoustic probe contains at least one microphone and one loudspeaker. The acoustic parameter determination of the ear canal is essential for the comparability of test-retest measurement situations. Compared to acoustic tubes, the ear canal wall cannot be described as a sound hard boundary. Sound energy is partly absorbed by the ear canal wall. In addition the ear canal features a complex geometric shape (Stinson and Lawton1). Those conditions are one reason for the inter individual variability in input impedance measurement data of the tympanic membrane. The method of Laser-Doppler-Vibrometry is well described in literature. Using this method, the surface velocity of vibrating bodies can be determined contact-free. Conventional Laser-Doppler-Systems (LDS) for auditory research are mounted on a surgical microscope. Assuming a free line of view to the ear drum, the handling of those laser-systems is complicated. We introduce the concept of a miniaturized vibrometer which is supposed to be applied directly in the ear canal for contact-free measurement of the tympanic membrane surface vibration. The proposed interferometer is based on a Fabry-Perot etalon with a DFB laser diode as light source. The fiber-based Fabry-Perot-interferometer is characterized by a reduced size, compared to e.g. Michelson-, or Mach-Zehnder-Systems. For the determination of the phase difference in the interferometer, a phase generated carrier was used. To fit the sensor head in the ear canal, the required shape of the probe was generated by means of the geometrical data of 70 ear molds. The suggested prototype is built up by a singlemode optical fiber with a GRIN-lens, acting as a fiber collimator. The probe has a diameter of 1.8 mm and a

"Swimmer's Ear" (Otitis Externa) Prevention

Science.gov (United States)

... infections, swimmer’s ear, and healthy swimming. "Swimmer's Ear" (Otitis Externa) What are the symptoms of swimmer's ear? ... Healthy page. Reference CDC. Estimated burden of acute otitis externa —United States, 2003–2007 . MMWR Morb Mortal ...

Ear Problems in Swimmers

Directory of Open Access Journals (Sweden)

Mao-Che Wang

2005-08-01

Full Text Available Acute diffuse otitis externa (swimmer's ear, otomycosis, exostoses, traumatic eardrum perforation, middle ear infection, and barotraumas of the inner ear are common problems in swimmers and people engaged in aqua activities. The most common ear problem in swimmers is acute diffuse otitis externa, with Pseudomonas aeruginosa being the most common pathogen. The symptoms are itching, otalgia, otorrhea, and conductive hearing loss. The treatment includes frequent cleansing of the ear canal, pain control, oral or topical medications, acidification of the ear canal, and control of predisposing factors. Swimming in polluted waters and ear-canal cleaning with cotton-tip applicators should be avoided. Exostoses are usually seen in people who swim in cold water and present with symptoms of accumulated debris, otorrhea and conductive hearing loss. The treatment for exostoses is transmeatal surgical removal of the tumors. Traumatic eardrum perforations may occur during water skiing or scuba diving and present with symptoms of hearing loss, otalgia, otorrhea, tinnitus and vertigo. Tympanoplasty might be needed if the perforations do not heal spontaneously. Patients with chronic otitis media with active drainage should avoid swimming, while patients who have undergone mastoidectomy and who have no cavity problems may swim. For children with ventilation tubes, surface swimming is safe in a clean, chlorinated swimming pool. Sudden sensorineural hearing loss and some degree of vertigo may occur after diving because of rupture of the round or oval window membrane.

Acoustic impedances of ear canals measured by impedance tube

DEFF Research Database (Denmark)

Ciric, Dejan; Hammershøi, Dorte

2007-01-01

During hearing sensitivity tests, the sound field is commonly generated by an earphone placed on a subject ear. One of the factors that can affect the sound transmission in the ear is the acoustic impedance of the ear canal. Its importance is related to the contribution of other elements involved...... in the transmission such as the earphone impedance. In order to determine the acoustic impedances of human ear canals, the standardized method for measurement of complex impedances used for the measurement of the audiometric earphone impedances is applied. It is based on the transfer function between two microphone...... locations in an impedance tube. The end of the tube representing the measurement plane is placed at the ear canal entrance. Thus, the impedance seen from the entrance inward is measured on 25 subjects. Most subjects participated in the previous measurement of the ratio between the pressures at the open...

Inertial Sensor-Based Gait Recognition: A Review

Science.gov (United States)

Sprager, Sebastijan; Juric, Matjaz B.

2015-01-01

With the recent development of microelectromechanical systems (MEMS), inertial sensors have become widely used in the research of wearable gait analysis due to several factors, such as being easy-to-use and low-cost. Considering the fact that each individual has a unique way of walking, inertial sensors can be applied to the problem of gait recognition where assessed gait can be interpreted as a biometric trait. Thus, inertial sensor-based gait recognition has a great potential to play an important role in many security-related applications. Since inertial sensors are included in smart devices that are nowadays present at every step, inertial sensor-based gait recognition has become very attractive and emerging field of research that has provided many interesting discoveries recently. This paper provides a thorough and systematic review of current state-of-the-art in this field of research. Review procedure has revealed that the latest advanced inertial sensor-based gait recognition approaches are able to sufficiently recognise the users when relying on inertial data obtained during gait by single commercially available smart device in controlled circumstances, including fixed placement and small variations in gait. Furthermore, these approaches have also revealed considerable breakthrough by realistic use in uncontrolled circumstances, showing great potential for their further development and wide applicability. PMID:26340634

Face recognition based on improved BP neural network

Directory of Open Access Journals (Sweden)

Yue Gaili

2017-01-01

Full Text Available In order to improve the recognition rate of face recognition, face recognition algorithm based on histogram equalization, PCA and BP neural network is proposed. First, the face image is preprocessed by histogram equalization. Then, the classical PCA algorithm is used to extract the features of the histogram equalization image, and extract the principal component of the image. And then train the BP neural network using the trained training samples. This improved BP neural network weight adjustment method is used to train the network because the conventional BP algorithm has the disadvantages of slow convergence, easy to fall into local minima and training process. Finally, the BP neural network with the test sample input is trained to classify and identify the face images, and the recognition rate is obtained. Through the use of ORL database face image simulation experiment, the analysis results show that the improved BP neural network face recognition method can effectively improve the recognition rate of face recognition.

Body lift, drag and power are relatively higher in large-eared than in small-eared bat species

DEFF Research Database (Denmark)

Håkansson, Jonas; Jakobsen, Lasse; Hedenström, Anders

2017-01-01

Bats navigate the dark using echolocation. Echolocation is enhanced by external ears, but external ears increase the projected frontal area and reduce the streamlining of the animal. External ears are thus expected to compromise flight efficiency, but research suggests that very large ears may mi....... The result of this trade-off would be the eco-morphological correlation in bat flight, with large-eared bats generally adopting slow-flight feeding strategies....

An image-based automatic recognition method for the flowering stage of maize

Science.gov (United States)

Yu, Zhenghong; Zhou, Huabing; Li, Cuina

2018-03-01

In this paper, we proposed an image-based approach for automatic recognizing the flowering stage of maize. A modified HOG/SVM detection framework is first adopted to detect the ears of maize. Then, we use low-rank matrix recovery technology to precisely extract the ears at pixel level. At last, a new feature called color gradient histogram, as an indicator, is proposed to determine the flowering stage. Comparing experiment has been carried out to testify the validity of our method and the results indicate that our method can meet the demand for practical observation.

Ear-to-Ear On-Body Channel Model for Hearing Aid Applications

DEFF Research Database (Denmark)

Kvist, Søren Helstrup; Thaysen, Jesper; Jakobsen, Kaj Bjarne

2015-01-01

that the head is mod- eled more accurately, and the radiation pattern is sampled in more points. The model is able to take the on-body radiation pattern of the antenna, as well as arbitrary he ad contours into account. The model is validated by the use of measurements and Ansys HFSS simulations on the specific......The deterministic ear-to-ear on-body channel is modeled by the use of a number of elliptically shaped paths. The semi-major axes of the elliptica lly shaped paths are adjusted such that they trace the outline of the head. The path gain converges when the number of paths is increased, su ch...... anthropomorphic mannequin (SAM) head. The model is used with a g enetic algorithm in order to synthesize a radiation pattern that is optimal for use with the ear-to-ear on-body channel. The radiation pattern is synthesized in terms of the spherical wave expansion coefficients of the hypothetical small antenna...

Supervised Filter Learning for Representation Based Face Recognition.

Directory of Open Access Journals (Sweden)

Chao Bi

Full Text Available Representation based classification methods, such as Sparse Representation Classification (SRC and Linear Regression Classification (LRC have been developed for face recognition problem successfully. However, most of these methods use the original face images without any preprocessing for recognition. Thus, their performances may be affected by some problematic factors (such as illumination and expression variances in the face images. In order to overcome this limitation, a novel supervised filter learning algorithm is proposed for representation based face recognition in this paper. The underlying idea of our algorithm is to learn a filter so that the within-class representation residuals of the faces' Local Binary Pattern (LBP features are minimized and the between-class representation residuals of the faces' LBP features are maximized. Therefore, the LBP features of filtered face images are more discriminative for representation based classifiers. Furthermore, we also extend our algorithm for heterogeneous face recognition problem. Extensive experiments are carried out on five databases and the experimental results verify the efficacy of the proposed algorithm.

Primitive Based Action Representation and recognition

DEFF Research Database (Denmark)

Baby, Sanmohan

The presented work is aimed at designing a system that will model and recognize actions and its interaction with objects. Such a system is aimed at facilitating robot task learning. Activity modeling and recognition is very important for its potential applications in surveillance, human-machine i......The presented work is aimed at designing a system that will model and recognize actions and its interaction with objects. Such a system is aimed at facilitating robot task learning. Activity modeling and recognition is very important for its potential applications in surveillance, human......-machine interface, entertainment, biomechanics etc. Recent developments in neuroscience suggest that all actions are a compositions of smaller units called primitives. Current works based on primitives for action recognition uses a supervised framework for specifying the primitives. We propose a method to extract...... primitives automatically. These primitives are to be used to generate actions based on certain rules for combining. These rules are expressed as a stochastic context free grammar. A model merging approach is adopted to learn a Hidden Markov Model to t the observed data sequences. The states of the HMM...

Structure and function of the mammalian middle ear. I: Large middle ears in small desert mammals.

Science.gov (United States)

Mason, Matthew J

2016-02-01

Many species of small desert mammals are known to have expanded auditory bullae. The ears of gerbils and heteromyids have been well described, but much less is known about the middle ear anatomy of other desert mammals. In this study, the middle ears of three gerbils (Meriones, Desmodillus and Gerbillurus), two jerboas (Jaculus) and two sengis (elephant-shrews: Macroscelides and Elephantulus) were examined and compared, using micro-computed tomography and light microscopy. Middle ear cavity expansion has occurred in members of all three groups, apparently in association with an essentially 'freely mobile' ossicular morphology and the development of bony tubes for the middle ear arteries. Cavity expansion can occur in different ways, resulting in different subcavity patterns even between different species of gerbils. Having enlarged middle ear cavities aids low-frequency audition, and several adaptive advantages of low-frequency hearing to small desert mammals have been proposed. However, while Macroscelides was found here to have middle ear cavities so large that together they exceed brain volume, the bullae of Elephantulus are considerably smaller. Why middle ear cavities are enlarged in some desert species but not others remains unclear, but it may relate to microhabitat. © 2015 Anatomical Society.

Effect of speechreading in presbycusis: Do we have a third ear?

Science.gov (United States)

Reis, Luis Roque; Escada, Pedro

2017-12-30

Evidence regarding the effect of speechreading is lacking in age-related hearing loss (presbycusis). Thus, in individuals with presbycusis, this study determined whether speechreading would improve word intelligibility. Moreover, the study investigated the effect of speechreading on word intelligibility depending on hearing impairment severity. This analytical, cross-sectional study involved two groups of individuals aged > 65 years that were enrolled by convenience sampling: 29 individuals with bilateral sensorineural hearing loss compatible with presbycusis (n=58 ears; mean age, 74.1±9.4 years) and 10 controls with at-most-mild hearing loss (n=58 ears; mean age, 73.8±8.5 years). All participants underwent a comprehensive medical and audiological evaluation, which included speech audiometry with and without observation of the audiologist's face, i.e. speechreading. Within each group, the effect of speechreading was determined as a change in the speech reception threshold. For all statistical analyses, p < 0.05 was considered significant. Both in individuals with presbycusis and controls, speechreading significantly improved speech discrimination (p<.001<.05); however, compared to controls, this effect of speechreading on speech discrimination was more pronounced in individuals with presbycusis (p<.001). Individuals with presbycusis or hearing impairment displayed improved spoken-word intelligibility when spoken-word recognition was coupled with speechreading. Thus, speechreading may serve as a "third ear".

Registration of 3D spectral OCT volumes using 3D SIFT feature point matching

Science.gov (United States)

Niemeijer, Meindert; Garvin, Mona K.; Lee, Kyungmoo; van Ginneken, Bram; Abràmoff, Michael D.; Sonka, Milan

2009-02-01

The recent introduction of next generation spectral OCT scanners has enabled routine acquisition of high resolution, 3D cross-sectional volumetric images of the retina. 3D OCT is used in the detection and management of serious eye diseases such as glaucoma and age-related macular degeneration. For follow-up studies, image registration is a vital tool to enable more precise, quantitative comparison of disease states. This work presents a registration method based on a recently introduced extension of the 2D Scale-Invariant Feature Transform (SIFT) framework1 to 3D.2 The SIFT feature extractor locates minima and maxima in the difference of Gaussian scale space to find salient feature points. It then uses histograms of the local gradient directions around each found extremum in 3D to characterize them in a 4096 element feature vector. Matching points are found by comparing the distance between feature vectors. We apply this method to the rigid registration of optic nerve head- (ONH) and macula-centered 3D OCT scans of the same patient that have only limited overlap. Three OCT data set pairs with known deformation were used for quantitative assessment of the method's robustness and accuracy when deformations of rotation and scaling were considered. Three-dimensional registration accuracy of 2.0+/-3.3 voxels was observed. The accuracy was assessed as average voxel distance error in N=1572 matched locations. The registration method was applied to 12 3D OCT scans (200 x 200 x 1024 voxels) of 6 normal eyes imaged in vivo to demonstrate the clinical utility and robustness of the method in a real-world environment.

Interpreting and responding to the Johannine feeding narrative: An empirical study in the SIFT hermeneutical method amongst Anglican ministry training candidates

Directory of Open Access Journals (Sweden)

Leslie J. Francis

2012-08-01

Full Text Available Drawing on Jungian psychological type theory, the SIFT method of biblical hermeneutics and liturgical preaching maintains that different psychological type preferences are associated with distinctive readings of scripture. In the present study this theory was tested amongst two groups of ministry training candidates (a total of 26 participants who were located within working groups according to their psychological type preferences, and invited to reflect on the Johannine feeding narrative (Jn 6:4−22, and to document their discussion. Analysis of these data provided empirical support for the theory underpinning the SIFT method.

Event Recognition Based on Deep Learning in Chinese Texts.

Directory of Open Access Journals (Sweden)

Yajun Zhang

Full Text Available Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM. Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN, then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%.

Event Recognition Based on Deep Learning in Chinese Texts.

Science.gov (United States)

Zhang, Yajun; Liu, Zongtian; Zhou, Wen

2016-01-01

Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM). Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN), then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%.

Serous otitis media (S.O.M.). A bacteriological study of the ear canal and the middle ear

NARCIS (Netherlands)

Cabenda, S. I.; Peerbooms, P. G.; van Asselt, G. J.; Feenstra, L.; van der Baan, S.

1988-01-01

A bacteriological study of the middle-ear effusions and the ear canals in children with chronic serous otitis media (S.O.M.) was performed. Sixty-eight children (127 ears) were investigated. From this study it appeared that cleansing of the ear canal with 0.5% chlorhexidine in 70% ethanol for 30 s

A knowledge-based approach for recognition of handwritten Pitman ...

Indian Academy of Sciences (India)

The paper describes a knowledge-based approach for the recognition of PSL strokes. Information about location and the direction of the starting point and final point of strokes are considered the knowledge base for recognition of strokes. The work comprises preprocessing, determination of starting and final points, ...

Matching score based face recognition

NARCIS (Netherlands)

Boom, B.J.; Beumer, G.M.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

2006-01-01

Accurate face registration is of vital importance to the performance of a face recognition algorithm. We propose a new method: matching score based face registration, which searches for optimal alignment by maximizing the matching score output of a classifier as a function of the different

How minute sooglossid frogs hear without a middle ear.

Science.gov (United States)

Boistel, Renaud; Aubin, Thierry; Cloetens, Peter; Peyrin, Françoise; Scotti, Thierry; Herzog, Philippe; Gerlach, Justin; Pollet, Nicolas; Aubry, Jean-François

2013-09-17

Acoustic communication is widespread in animals. According to the sensory drive hypothesis [Endler JA (1993) Philos Trans R Soc Lond B Biol Sci 340(1292):215-225], communication signals and perceptual systems have coevolved. A clear illustration of this is the evolution of the tetrapod middle ear, adapted to life on land. Here we report the discovery of a bone conduction-mediated stimulation of the ear by wave propagation in Sechellophryne gardineri, one of the world's smallest terrestrial tetrapods, which lacks a middle ear yet produces acoustic signals. Based on X-ray synchrotron holotomography, we measured the biomechanical properties of the otic tissues and modeled the acoustic propagation. Our models show how bone conduction enhanced by the resonating role of the mouth allows these seemingly deaf frogs to communicate effectively without a middle ear.

Facial Expression Recognition Based on TensorFlow Platform

Directory of Open Access Journals (Sweden)

Xia Xiao-Ling

2017-01-01

Full Text Available Facial expression recognition have a wide range of applications in human-machine interaction, pattern recognition, image understanding, machine vision and other fields. Recent years, it has gradually become a hot research. However, different people have different ways of expressing their emotions, and under the influence of brightness, background and other factors, there are some difficulties in facial expression recognition. In this paper, based on the Inception-v3 model of TensorFlow platform, we use the transfer learning techniques to retrain facial expression dataset (The Extended Cohn-Kanade dataset, which can keep the accuracy of recognition and greatly reduce the training time.

Vision-Based Recognition of Activities by a Humanoid Robot

Directory of Open Access Journals (Sweden)

Mounîm A. El-Yacoubi

2015-12-01

Full Text Available We present an autonomous assistive robotic system for human activity recognition from video sequences. Due to the large variability inherent to video capture from a non-fixed robot (as opposed to a fixed camera, as well as the robot's limited computing resources, implementation has been guided by robustness to this variability and by memory and computing speed efficiency. To accommodate motion speed variability across users, we encode motion using dense interest point trajectories. Our recognition model harnesses the dense interest point bag-of-words representation through an intersection kernel-based SVM that better accommodates the large intra-class variability stemming from a robot operating in different locations and conditions. To contextually assess the engine as implemented in the robot, we compare it with the most recent approaches of human action recognition performed on public datasets (non-robot-based, including a novel approach of our own that is based on a two-layer SVM-hidden conditional random field sequential recognition model. The latter's performance is among the best within the recent state of the art. We show that our robot-based recognition engine, while less accurate than the sequential model, nonetheless shows good performances, especially given the adverse test conditions of the robot, relative to those of a fixed camera.

Smartphone based face recognition tool for the blind.

Science.gov (United States)

Kramer, K M; Hedin, D S; Rolkosky, D J

2010-01-01

The inability to identify people during group meetings is a disadvantage for blind people in many professional and educational situations. To explore the efficacy of face recognition using smartphones in these settings, we have prototyped and tested a face recognition tool for blind users. The tool utilizes Smartphone technology in conjunction with a wireless network to provide audio feedback of the people in front of the blind user. Testing indicated that the face recognition technology can tolerate up to a 40 degree angle between the direction a person is looking and the camera's axis and a 96% success rate with no false positives. Future work will be done to further develop the technology for local face recognition on the smartphone in addition to remote server based face recognition.

The effect of different sowing depths on fresh ear yield and some ear characteristics of sweet corn

Directory of Open Access Journals (Sweden)

Bekir Atar

2017-12-01

Full Text Available The research was conducted with aim to investigate effect on fresh ear yield and some ear characteristics of sweet corn of sowing at different depths during 2015 and 2016 years in Isparta. The experiments were set up according to randomized complete block design with three replicates using BATEM TATLI sweet corn cultivar. Furrows were opened at depths of 10 and 20 cm after the soil preparation, and seeds were sown in the 4-5 cm depth in to these furrows. According to means of years, while furrow sowing increased ear diameter, ear weigh, number of kernels per ear and fresh ear yield compared to control, it was not effect on ear length. In the research, between 10 cm and 20 cm furrow sowing wasn’t significant statistically. Fresh ear yield in control, 10 cm and 20 cm furrow sowing were measured as 1110.9 kg ha-1 , 1228.4 kg ha-1 and 1289.4 kg ha-1 , respectively. According to results of research, 5 cm deep sowing in 10 cm furrows should be advised in sweet corn cultivation.

Ear Infection and Vaccines

Science.gov (United States)

... an ENT Doctor Near You Ear Infection and Vaccines Ear Infection and Vaccines Patient Health Information News ... or may need reinsertion over time. What about vaccines? A vaccine is a preparation administered to stimulate ...

Swimmer's Ear (For Parents)

Science.gov (United States)

... Development Infections Diseases & Conditions Pregnancy & Baby Nutrition & Fitness Emotions & Behavior School & Family Life First Aid & Safety Doctors & ... can lead to an infection. Dry skin or eczema , scratching the ear canal, vigorous ear cleaning with ...

Analysis of earing behaviour in deep drawing of ASS 304 at elevated temperature

Science.gov (United States)

Gupta, Amit Kumar; Deole, Aditya; Kotkunde, Nitin; Singh, Swadesh Kumar; jella, Gangadhar

2016-08-01

Earing tendency in a deep drawn cup of circular blanks is one the most prominent characteristics observed due to anisotropy in a metal sheet. Such formation of uneven rim is mainly due to dissimilarity in yield stress as well as Lankford parameter (r- value) in different orientations. In this paper, an analytical function coupled with different yield functions viz., Hill 1948, Barlat 1989 and Barlat Yld 2000-2d has been used to provide an approximation of earing profile. In order to validate the results, material parameters for yield functions and hardening rule have been calibrated for ASS 304 at 250°C and deep drawing experiment is conducted to measure the earing profile. The predicted earing profiles based on analytical results have been validated using experimental earing profile. Based on this analysis, Barlat Yld 2000-2d has been observed to be a well suited yield model for deep drawing of ASS 304, which also confirms the reliability of analytical function for earing profile estimation.

A Review on Video-Based Human Activity Recognition

Directory of Open Access Journals (Sweden)

Shian-Ru Ke

2013-06-01

Full Text Available This review article surveys extensively the current progresses made toward video-based human activity recognition. Three aspects for human activity recognition are addressed including core technology, human activity recognition systems, and applications from low-level to high-level representation. In the core technology, three critical processing stages are thoroughly discussed mainly: human object segmentation, feature extraction and representation, activity detection and classification algorithms. In the human activity recognition systems, three main types are mentioned, including single person activity recognition, multiple people interaction and crowd behavior, and abnormal activity recognition. Finally the domains of applications are discussed in detail, specifically, on surveillance environments, entertainment environments and healthcare systems. Our survey, which aims to provide a comprehensive state-of-the-art review of the field, also addresses several challenges associated with these systems and applications. Moreover, in this survey, various applications are discussed in great detail, specifically, a survey on the applications in healthcare monitoring systems.

Sub-pattern based multi-manifold discriminant analysis for face recognition

Science.gov (United States)

Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen

2018-04-01

In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.

Facial expression recognition based on improved deep belief networks

Science.gov (United States)

Wu, Yao; Qiu, Weigen

2017-08-01

In order to improve the robustness of facial expression recognition, a method of face expression recognition based on Local Binary Pattern (LBP) combined with improved deep belief networks (DBNs) is proposed. This method uses LBP to extract the feature, and then uses the improved deep belief networks as the detector and classifier to extract the LBP feature. The combination of LBP and improved deep belief networks is realized in facial expression recognition. In the JAFFE (Japanese Female Facial Expression) database on the recognition rate has improved significantly.

Carcinoid tumour of the middle ear

LENUS (Irish Health Repository)

Baig, Salman

2012-09-01

A case of middle ear mass in a young female from Ireland is described, who presented with left ear hearing loss and intermittent bloody discharge from the same ear. Examination under microscope revealed occlusive polyp in the left ear and a biopsy had been taken under general anaesthesia. Histopathology report described an adenoma \\/ carcinoid tumour of the middle ear confirmed by positive immunohistochemical staining. CT temporal bones revealed the extension of the disease. The patient underwent left tympanotomy and excision of the tumour. In general, these tumours are regarded as benign but may be mistaken for adenocarcinomas because of their histological heterogenecity.

Support vector machine-based facial-expression recognition method combining shape and appearance

Science.gov (United States)

Han, Eun Jung; Kang, Byung Jun; Park, Kang Ryoung; Lee, Sangyoun

2010-11-01

Facial expression recognition can be widely used for various applications, such as emotion-based human-machine interaction, intelligent robot interfaces, face recognition robust to expression variation, etc. Previous studies have been classified as either shape- or appearance-based recognition. The shape-based method has the disadvantage that the individual variance of facial feature points exists irrespective of similar expressions, which can cause a reduction of the recognition accuracy. The appearance-based method has a limitation in that the textural information of the face is very sensitive to variations in illumination. To overcome these problems, a new facial-expression recognition method is proposed, which combines both shape and appearance information, based on the support vector machine (SVM). This research is novel in the following three ways as compared to previous works. First, the facial feature points are automatically detected by using an active appearance model. From these, the shape-based recognition is performed by using the ratios between the facial feature points based on the facial-action coding system. Second, the SVM, which is trained to recognize the same and different expression classes, is proposed to combine two matching scores obtained from the shape- and appearance-based recognitions. Finally, a single SVM is trained to discriminate four different expressions, such as neutral, a smile, anger, and a scream. By determining the expression of the input facial image whose SVM output is at a minimum, the accuracy of the expression recognition is much enhanced. The experimental results showed that the recognition accuracy of the proposed method was better than previous researches and other fusion methods.

Iris recognition based on robust principal component analysis

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Karn, Pradeep; He, Xiao Hai; Yang, Shuai; Wu, Xiao Hong

2014-11-01

Iris images acquired under different conditions often suffer from blur, occlusion due to eyelids and eyelashes, specular reflection, and other artifacts. Existing iris recognition systems do not perform well on these types of images. To overcome these problems, we propose an iris recognition method based on robust principal component analysis. The proposed method decomposes all training images into a low-rank matrix and a sparse error matrix, where the low-rank matrix is used for feature extraction. The sparsity concentration index approach is then applied to validate the recognition result. Experimental results using CASIA V4 and IIT Delhi V1iris image databases showed that the proposed method achieved competitive performances in both recognition accuracy and computational efficiency.

Academic Freedom on Trial: 100 Years of Sifting and Winnowing at the University of Wisconsin-Madison.

Science.gov (United States)

Hansen, W. Lee, Ed.

The 29 papers in this collection celebrate academic freedom at the University of Wisconsin-Madison and are organized around the 1894 "trial" of Richard T. Ely, an economist who was exonerated of fomenting unrest and discussing "dangerous" ideas in a Board of Regents Statement which stressed the importance of "sifting and…

A recognition method research based on the heart sound texture map

Directory of Open Access Journals (Sweden)

Huizhong Cheng

2016-06-01

Full Text Available In order to improve the Heart Sound recognition rate and reduce the recognition time, in this paper, we introduces a new method for Heart Sound pattern recognition by using Heart Sound Texture Map. Based on the Heart Sound model, we give the Heart Sound time-frequency diagram and the Heart Sound Texture Map definition, we study the structure of the Heart Sound Window Function principle and realization method, and then discusses how to use the Heart Sound Window Function and the Short-time Fourier Transform to obtain two-dimensional Heart Sound time-frequency diagram, propose corner correlation recognition algorithm based on the Heart Sound Texture Map according to the characteristics of Heart Sound. The simulation results show that the Heart Sound Window Function compared with the traditional window function makes the first (S1 and the second (S2 Heart Sound texture clearer. And the corner correlation recognition algorithm based on the Heart Sound Texture Map can significantly improve the recognition rate and reduce the expense, which is an effective Heart Sound recognition method.

Middle ear implants

Directory of Open Access Journals (Sweden)

K S Gangadhara Somayaji

2013-01-01

Full Text Available Hearing loss is becoming more common in the society living in cities with lot of background noise around, and frequent use of gadgets like mobile phones, MP3s, and IPods are adding to the problem. The loss may involve the conductive or perceptive pathway. Majority of the patients with conductive hearing loss will revert back to normal hearing levels with medical and/or surgical treatment. However, in sensorineural hearing loss, many factors are involved in the management. Though traditionally hearing aids in various forms are the most commonly used modality in managing these patients, there are some drawbacks associated with them. Implantable middle ear amplifiers represent the most recent breakthrough in the management of hearing loss. Middle ear implants are surgically implanted electronic devices that aim to correct hearing loss by stimulating the ossicular chain or middle ear. Of late, they are also being used in the management of congenital conductive hearing loss and certain cases of chronic otitis media with residual hearing loss. The article aims to provide general information about the technology, indications and contraindications, selection of candidates, available systems, and advantages of middle ear implants. (MEI

Minimising the Effects of Isobaric Product Ions in SIFT-MS Quantification of Acetaldehyde, Dimethyl Sulphide and Carbon Dioxide

Czech Academy of Sciences Publication Activity Database

Smith, D.; Chippendale, T. W. E.; Španěl, Patrik

2013-01-01

Roč. 9, č. 4 (2013), s. 550-557 ISSN 1573-4110 Institutional support: RVO:61388955 Keywords : selected ion flow tube mass spectrometry * SIFT-MS * acetaldehyde Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 1.194, year: 2013

Embedded wavelet-based face recognition under variable position

Science.gov (United States)

Cotret, Pascal; Chevobbe, Stéphane; Darouich, Mehdi

2015-02-01

For several years, face recognition has been a hot topic in the image processing field: this technique is applied in several domains such as CCTV, electronic devices delocking and so on. In this context, this work studies the efficiency of a wavelet-based face recognition method in terms of subject position robustness and performance on various systems. The use of wavelet transform has a limited impact on the position robustness of PCA-based face recognition. This work shows, for a well-known database (Yale face database B*), that subject position in a 3D space can vary up to 10% of the original ROI size without decreasing recognition rates. Face recognition is performed on approximation coefficients of the image wavelet transform: results are still satisfying after 3 levels of decomposition. Furthermore, face database size can be divided by a factor 64 (22K with K = 3). In the context of ultra-embedded vision systems, memory footprint is one of the key points to be addressed; that is the reason why compression techniques such as wavelet transform are interesting. Furthermore, it leads to a low-complexity face detection stage compliant with limited computation resources available on such systems. The approach described in this work is tested on three platforms from a standard x86-based computer towards nanocomputers such as RaspberryPi and SECO boards. For K = 3 and a database with 40 faces, the execution mean time for one frame is 0.64 ms on a x86-based computer, 9 ms on a SECO board and 26 ms on a RaspberryPi (B model).

Enhancement of Iris Recognition System Based on Phase Only Correlation

Directory of Open Access Journals (Sweden)

Nuriza Pramita

2011-08-01

Full Text Available Iris recognition system is one of biometric based recognition/identification systems. Numerous techniques have been implemented to achieve a good recognition rate, including the ones based on Phase Only Correlation (POC. Significant and higher correlation peaks suggest that the system recognizes iris images of the same subject (person, while lower and unsignificant peaks correspond to recognition of those of difference subjects. Current POC methods have not investigated minimum iris point that can be used to achieve higher correlation peaks. This paper proposed a method that used only one-fourth of full normalized iris size to achieve higher (or at least the same recognition rate. Simulation on CASIA version 1.0 iris image database showed that averaged recognition rate of the proposed method achieved 67%, higher than that of using one-half (56% and full (53% iris point. Furthermore, all (100% POC peak values of the proposed method was higher than that of the method with full iris points.

Listening to the ear

Science.gov (United States)

Shera, Christopher A.

Otoacoustic emissions demonstrate that the ear creates sound while listening to sound, offering a promising acoustic window on the mechanics of hearing in awake, listening human beings. That window is clouded, however, by an incomplete knowledge of wave reflection and transmission, both forth and back within the cochlea and through the middle ear. This thesis "does windows," addressing wave propagation and scattering on both sides of the middle ear. A summary of highlights follows. Measurements of the cochlear input impedance in cat are used to identify a new symmetry in cochlear mechanics-termed "tapering symmetry" after its geometric interpretation in simple models-that guarantees that the wavelength of the traveling wave changes slowly with position near the stapes. Waves therefore propagate without reflection through the basal turns of the cochlea. Analytic methods for solving the cochlear wave equations using a perturbative scattering series are given and used to demonstrate that, contrary to common belief, conventional cochlear models exhibit negligible internal reflection whether or not they accurately represent the tapering symmetries of the inner ear. Frameworks for the systematic "deconstruction" of eardrum and middle-ear transduction characteristics are developed and applied to the analysis of noninvasive measurements of middle-ear and cochlear mechanics. A simple phenomenological model of inner-ear compressibility that correctly predicts hearing thresholds in patients with missing or disarticulated middle-ear ossicles is developed and used to establish an upper bound on cochlear compressibility several orders of magnitude smaller than that provided by direct measurements. Accurate measurements of stimulus frequency evoked otoacoustic emissions are performed and used to determine the form and frequency variation of the cochlear traveling-wave ratio noninvasively. Those measurements are inverted to obtain the spatial distribution of mechanical

Prevalence of external ear disorders in Belgian stray cats.

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Bollez, Anouck; de Rooster, Hilde; Furcas, Alessandra; Vandenabeele, Sophie

2018-02-01

Objectives Feline otitis externa is a multifactorial dermatological disorder about which very little is known. The objective of this study was to map the prevalence of external ear canal disorders and the pathogens causing otitis externa in stray cats roaming around the region of Ghent, Belgium. Methods One hundred and thirty stray cats were randomly selected during a local trap-neuter-return programme. All cats were European Shorthairs. This study included clinical, otoscopic and cytological evaluation of both external ears of each cat. Prospective data used as parameters in this study included the sex, age and body condition score of each cat, as well as the presence of nasal and/or ocular discharge, and the results of feline immunodeficiency virus (FIV) and feline leukaemia virus (FeLV) Snap tests. Results Remarkably, very few (sub)clinical problems of the external ear canal were found in the stray cat population. Malassezia species was by far the most common organism found in the external ear canals of the 130 stray cats. A total of 96/130 (74%) cats were found to have Malassezia species organisms present in one or both ears based on the cytological examination. No correlation was found between the parameters of sex, age, body condition score, the presence of nasal and/or ocular discharge and FIV and FeLV status, and the presence of parasites, bacteria or yeasts. Conclusions and relevance This study provides more information about the normal state of the external ear canal of stray cats. The ears of most stray cats are relatively healthy. The presence of Malassezia species organisms in the external ear canal is not rare among stray cats.

The Hierarchical Specification and Mechanical Verification of the SIFT Design

Science.gov (United States)

1983-01-01

The formal specification and proof methodology employed to demonstrate that the SIFT computer system meets its requirements are described. The hierarchy of design specifications is shown, from very abstract descriptions of system function down to the implementation. The most abstract design specifications are simple and easy to understand, almost all details of the realization were abstracted out, and are used to ensure that the system functions reliably and as intended. A succession of lower level specifications refines these specifications into more detailed, and more complex, views of the system design, culminating in the Pascal implementation. The section describes the rigorous mechanical proof that the abstract specifications are satisfied by the actual implementation.

Specific and Class Object Recognition for Service Robots through Autonomous and Interactive Methods

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Mansur, Al; Kuno, Yoshinori

Service robots need to be able to recognize and identify objects located within complex backgrounds. Since no single method may work in every situation, several methods need to be combined and robots have to select the appropriate one automatically. In this paper we propose a scheme to classify situations depending on the characteristics of the object of interest and user demand. We classify situations into four groups and employ different techniques for each. We use Scale-invariant feature transform (SIFT), Kernel Principal Components Analysis (KPCA) in conjunction with Support Vector Machine (SVM) using intensity, color, and Gabor features for five object categories. We show that the use of appropriate features is important for the use of KPCA and SVM based techniques on different kinds of objects. Through experiments we show that by using our categorization scheme a service robot can select an appropriate feature and method, and considerably improve its recognition performance. Yet, recognition is not perfect. Thus, we propose to combine the autonomous method with an interactive method that allows the robot to recognize the user request for a specific object and class when the robot fails to recognize the object. We also propose an interactive way to update the object model that is used to recognize an object upon failure in conjunction with the user's feedback.

A feature extraction algorithm based on corner and spots in self-driving vehicles

Directory of Open Access Journals (Sweden)

Yupeng FENG

2017-06-01

Full Text Available To solve the poor real-time performance problem of the visual odometry based on embedded system with limited computing resources, an image matching method based on Harris and SIFT is proposed, namely the Harris-SIFT algorithm. On the basis of the review of SIFT algorithm, the principle of Harris-SIFT algorithm is provided. First, Harris algorithm is used to extract the corners of the image as candidate feature points, and scale invariant feature transform (SIFT features are extracted from those candidate feature points. At last, through an example, the algorithm is simulated by Matlab, then the complexity and other performance of the algorithm are analyzed. The experimental results show that the proposed method reduces the computational complexity and improves the speed of feature extraction. Harris-SIFT algorithm can be used in the real-time vision odometer system, and will bring about a wide application of visual odometry in embedded navigation system.

Gait Recognition Based on Outermost Contour

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Lili Liu

2011-10-01

Full Text Available Gait recognition aims to identify people by the way they walk. In this paper, a simple but e ective gait recognition method based on Outermost Contour is proposed. For each gait image sequence, an adaptive silhouette extraction algorithm is firstly used to segment the frames of the sequence and a series of postprocessing is applied to obtain the normalized silhouette images with less noise. Then a novel feature extraction method based on Outermost Contour is performed. Principal Component Analysis (PCA is adopted to reduce the dimensionality of the distance signals derived from the Outermost Contours of silhouette images. Then Multiple Discriminant Analysis (MDA is used to optimize the separability of gait features belonging to di erent classes. Nearest Neighbor (NN classifier and Nearest Neighbor classifier with respect to class Exemplars (ENN are used to classify the final feature vectors produced by MDA. In order to verify the e ectiveness and robustness of our feature extraction algorithm, we also use two other classifiers: Backpropagation Neural Network (BPNN and Support Vector Machine (SVM for recognition. Experimental results on a gait database of 100 people show that the accuracy of using MDA, BPNN and SVM can achieve 97.67%, 94.33% and 94.67%, respectively.

Characteristics of laser-induced shock wave injury to the inner ear of rats

Science.gov (United States)

Kurioka, Takaomi; Matsunobu, Takeshi; Niwa, Katsuki; Tamura, Atsushi; Kawauchi, Satoko; Satoh, Yasushi; Sato, Shunichi; Shiotani, Akihiro

2014-12-01

Recently, the number of blast injuries of the inner ear has increased in the general population. In blast-induced inner ear injury, a shock wave (SW) component in the blast wave is considered to play an important role in sensorineural hearing loss. However, the mechanisms by which an SW affects inner ear tissue remain largely unknown. We aimed to establish a new animal model for SW-induced inner ear injury by using laser-induced SWs (LISWs) on rats. The LISWs were generated by irradiating an elastic laser target with 694-nm nanosecond pulses of a ruby laser. After LISW application to the cochlea through bone conduction, auditory measurements revealed the presence of inner ear dysfunction, the extent of which depended on LISW overpressure. A significantly lower survival rate of hair cells and spiral ganglion neurons, as well as severe oxidative damage, were observed in the inner ear exposed to an LISW. Although considerable differences in the pressure characteristics exist between LISWs and SWs in real blast waves, the functional and morphological changes shown by the present LISW-based model were similar to those observed in real blast-induced injury. Thus, our animal model is expected to be useful for laboratory-based research of blast-induced inner ear injury.

Characteristics of laser-induced shock wave injury to the inner ear of rats.

Science.gov (United States)

Kurioka, Takaomi; Matsunobu, Takeshi; Niwa, Katsuki; Tamura, Atsushi; Kawauchi, Satoko; Satoh, Yasushi; Sato, Shunichi; Shiotani, Akihiro

2014-12-01

Recently, the number of blast injuries of the inner ear has increased in the general population. In blast-induced inner ear injury, a shock wave (SW) component in the blast wave is considered to play an important role in sensorineural hearing loss. However, the mechanisms by which an SW affects inner ear tissue remain largely unknown. We aimed to establish a new animal model for SW-induced inner ear injury by using laser-induced SWs (LISWs) on rats. The LISWs were generated by irradiating an elastic laser target with 694-nm nanosecond pulses of a ruby laser. After LISW application to the cochlea through bone conduction, auditory measurements revealed the presence of inner ear dysfunction, the extent of which depended on LISW overpressure. A significantly lower survival rate of hair cells and spiral ganglion neurons, as well as severe oxidative damage, were observed in the inner ear exposed to an LISW. Although considerable differences in the pressure characteristics exist between LISWs and SWs in real blast waves, the functional and morphological changes shown by the present LISW-based model were similar to those observed in real blast-induced injury. Thus, our animal model is expected to be useful for laboratory-based research of blast-induced inner ear injury.

Topical ear drop self-medication practice among the Ear, Nose, and Throat patients in Ido Ekiti, Nigeria: A cross - sectional study.

Science.gov (United States)

Olajide, Toye Gabriel; Aremu, Kayode Shuaib; Esan, Olaide T; Dosunmu, Adepeju Oluwatona; Raji, Mustapha Muhammad

2018-01-01

Self-medication is a common habit in our country; Nigeria, especially among patients with otorhinolaryngological disorders. Medication when taken wrongly may bring dire consequences to the individual, such as masking developing diseases and may cause many other undesirable effects. The aim of this study was to determine the prevalence and to analyze topical ear drop self-medication practices among respondents attending the Ear, Nose, and Throat Clinic of Federal Teaching Hospital Ido Ekiti, Nigeria. A 6-month hospital based cross-sectional study was conducted among patients who were seen in the Ear, Nose, and Throat facility of Federal Teaching Hospital, Ido Ekiti from July to December 2016 to determine topical ear drop self-medication practices. A pretested semi-structured questionnaire was used to obtained information from respondents. A total of 162 respondents out of 493 patients seen during the study had otological problems. Of which 107 (66%) respondents had engaged in self-medication with topical ear drops. Their ages ranged between 2 and 83 years with a mean age of 36.6 ± 19.1 years. There were 75 males and 87 females. The major reason for self-medication was that their ailments were minor in about 40.2% and the most common indication for self-medication was ear blockage with hearing impairment (33.6%). Pharmacy/chemist shops (42%) were major sources of information for those that self-medicated. Chloramphenicol and gentamycin were the major drugs that were used by the respondents. Majority of the respondents in this study practiced self-medication using different topical ear drops. Major source of information on the topical ear drops used was from pharmacy/chemist shops. There is a need for adequate public health education to create awareness among people on the danger of self-medication and to enact or enforce the law to reduce access to over the counter drugs. Healthcare should be made available and avoidable at primary health-care level.

A SIFT Study of the Reactions of H2ONO+ Ions with Several Types of Organic Molecules

Czech Academy of Sciences Publication Activity Database

Smith, D.; Wang, T.; Španěl, Patrik

2003-01-01

Roč. 230, č. 1 (2003), s. 1-9 ISSN 1387-3806 R&D Projects: GA ČR GA202/03/0827 Institutional research plan: CEZ:AV0Z4040901 Keywords : SIFT * nitrosohydronium ions * protonated nitrous acid Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.361, year: 2003

Can Loud Music Hurt My Ears?

Science.gov (United States)

... Videos for Educators Search English Español Can Loud Music Hurt My Ears? KidsHealth / For Kids / Can Loud Music Hurt My Ears? Print en español La música ... up? Oh! You want to know if loud music can hurt your ears . Are you asking because ...

A Comparison of Moments-Based Logo Recognition Methods

Directory of Open Access Journals (Sweden)

Zili Zhang

2014-01-01

Full Text Available Logo recognition is an important issue in document image, advertisement, and intelligent transportation. Although there are many approaches to study logos in these fields, logo recognition is an essential subprocess. Among the methods of logo recognition, the descriptor is very vital. The results of moments as powerful descriptors were not discussed before in terms of logo recognition. So it is unclear which moments are more appropriate to recognize which kind of logos. In this paper we find out the relations between logos with different transforms and moments, which moments are fit for logos with different transforms. The open datasets are employed from the University of Maryland. The comparisons based on moments are carried out from the aspects of logos with noise, and rotation, scaling, rotation and scaling.

Headphone-To-Ear Transfer Function Estimation Using Measured Acoustic Parameters

Directory of Open Access Journals (Sweden)

Jinlin Liu

2018-06-01

Full Text Available This paper proposes to use an optimal five-microphone array method to measure the headphone acoustic reflectance and equivalent sound sources needed in the estimation of headphone-to-ear transfer functions (HpTFs. The performance of this method is theoretically analyzed and experimentally investigated. With the measured acoustic parameters HpTFs for different headphones and ear canal area functions are estimated based on a computational acoustic model. The estimation results show that HpTFs vary considerably with headphones and ear canals, which suggests that individualized compensations for HpTFs are necessary for headphones to reproduce desired sounds for different listeners.

Multispectral iris recognition based on group selection and game theory

Science.gov (United States)

Ahmad, Foysal; Roy, Kaushik

2017-05-01

A commercially available iris recognition system uses only a narrow band of the near infrared spectrum (700-900 nm) while iris images captured in the wide range of 405 nm to 1550 nm offer potential benefits to enhance recognition performance of an iris biometric system. The novelty of this research is that a group selection algorithm based on coalition game theory is explored to select the best patch subsets. In this algorithm, patches are divided into several groups based on their maximum contribution in different groups. Shapley values are used to evaluate the contribution of patches in different groups. Results show that this group selection based iris recognition

Ear biometrics for patient identification in global health: a cross-sectional study to test the feasibility of a simplified algorithm.

Science.gov (United States)

Ragan, Elizabeth J; Johnson, Courtney; Milton, Jacqueline N; Gill, Christopher J

2016-11-02

One of the greatest public health challenges in low- and middle-income countries (LMICs) is identifying people over time and space. Recent years have seen an explosion of interest in developing electronic approaches to addressing this problem, with mobile technology at the forefront of these efforts. We investigate the possibility of biometrics as a simple, cost-efficient, and portable solution. Common biometrics approaches include fingerprinting, iris scanning and facial recognition, but all are less than ideal due to complexity, infringement on privacy, cost, or portability. Ear biometrics, however, proved to be a unique and viable solution. We developed an identification algorithm then conducted a cross sectional study in which we photographed left and right ears from 25 consenting adults. We then conducted re-identification and statistical analyses to identify the accuracy and replicability of our approach. Through principal component analysis, we found the curve of the ear helix to be the most reliable anatomical structure and the basis for re-identification. Although an individual ear allowed for high re-identification rate (88.3%), when both left and right ears were paired together, our rate of re-identification amidst the pool of potential matches was 100%. The results of this study have implications on future efforts towards building a biometrics solution for patient identification in LMICs. We provide a conceptual platform for further investigation into the development of an ear biometrics identification mobile application.

The Relative Success of Recognition-Based Inference in Multichoice Decisions

Science.gov (United States)

McCloy, Rachel; Beaman, C. Philip; Smith, Philip T.

2008-01-01

The utility of an "ecologically rational" recognition-based decision rule in multichoice decision problems is analyzed, varying the type of judgment required (greater or lesser). The maximum size and range of a counterintuitive advantage associated with recognition-based judgment (the "less-is-more effect") is identified for a range of cue…

On-line, real time monitoring of exhaled trace gases by SIFT-MS in the perioperative setting: a feasibility study

Czech Academy of Sciences Publication Activity Database

Boshier, P. R.; Cushnir, J. R.; Mistry, V.; Knaggs, A.; Španěl, Patrik; Smith, D.; Hanna, G. B.

2011-01-01

Roč. 136, č. 16 (2011), s. 3233-3237 ISSN 0003-2654 Institutional research plan: CEZ:AV0Z40400503 Keywords : SIFT-MS * breath analysis Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 4.230, year: 2011

An Evaluation of PC-Based Optical Character Recognition Systems.

Science.gov (United States)

Schreier, E. M.; Uslan, M. M.

1991-01-01

The review examines six personal computer-based optical character recognition (OCR) systems designed for use by blind and visually impaired people. Considered are OCR components and terms, documentation, scanning and reading, command structure, conversion, unique features, accuracy of recognition, scanning time, speed, and cost. (DB)

Uniform design based SVM model selection for face recognition

Science.gov (United States)

Li, Weihong; Liu, Lijuan; Gong, Weiguo

2010-02-01

Support vector machine (SVM) has been proved to be a powerful tool for face recognition. The generalization capacity of SVM depends on the model with optimal hyperparameters. The computational cost of SVM model selection results in application difficulty in face recognition. In order to overcome the shortcoming, we utilize the advantage of uniform design--space filling designs and uniformly scattering theory to seek for optimal SVM hyperparameters. Then we propose a face recognition scheme based on SVM with optimal model which obtained by replacing the grid and gradient-based method with uniform design. The experimental results on Yale and PIE face databases show that the proposed method significantly improves the efficiency of SVM model selection.

3D Printed Bionic Ears

Science.gov (United States)

Mannoor, Manu S.; Jiang, Ziwen; James, Teena; Kong, Yong Lin; Malatesta, Karen A.; Soboyejo, Winston O.; Verma, Naveen; Gracias, David H.; McAlpine, Michael C.

2013-01-01

The ability to three-dimensionally interweave biological tissue with functional electronics could enable the creation of bionic organs possessing enhanced functionalities over their human counterparts. Conventional electronic devices are inherently two-dimensional, preventing seamless multidimensional integration with synthetic biology, as the processes and materials are very different. Here, we present a novel strategy for overcoming these difficulties via additive manufacturing of biological cells with structural and nanoparticle derived electronic elements. As a proof of concept, we generated a bionic ear via 3D printing of a cell-seeded hydrogel matrix in the precise anatomic geometry of a human ear, along with an intertwined conducting polymer consisting of infused silver nanoparticles. This allowed for in vitro culturing of cartilage tissue around an inductive coil antenna in the ear, which subsequently enables readout of inductively-coupled signals from cochlea-shaped electrodes. The printed ear exhibits enhanced auditory sensing for radio frequency reception, and complementary left and right ears can listen to stereo audio music. Overall, our approach suggests a means to intricately merge biologic and nanoelectronic functionalities via 3D printing. PMID:23635097

3D printed bionic ears.

Science.gov (United States)

Mannoor, Manu S; Jiang, Ziwen; James, Teena; Kong, Yong Lin; Malatesta, Karen A; Soboyejo, Winston O; Verma, Naveen; Gracias, David H; McAlpine, Michael C

2013-06-12

The ability to three-dimensionally interweave biological tissue with functional electronics could enable the creation of bionic organs possessing enhanced functionalities over their human counterparts. Conventional electronic devices are inherently two-dimensional, preventing seamless multidimensional integration with synthetic biology, as the processes and materials are very different. Here, we present a novel strategy for overcoming these difficulties via additive manufacturing of biological cells with structural and nanoparticle derived electronic elements. As a proof of concept, we generated a bionic ear via 3D printing of a cell-seeded hydrogel matrix in the anatomic geometry of a human ear, along with an intertwined conducting polymer consisting of infused silver nanoparticles. This allowed for in vitro culturing of cartilage tissue around an inductive coil antenna in the ear, which subsequently enables readout of inductively-coupled signals from cochlea-shaped electrodes. The printed ear exhibits enhanced auditory sensing for radio frequency reception, and complementary left and right ears can listen to stereo audio music. Overall, our approach suggests a means to intricately merge biologic and nanoelectronic functionalities via 3D printing.

Modeling Analysis of Biomechanical Changes of Middle Ear and Cochlea in Otitis Media

Science.gov (United States)

Gan, Rong Z.; Zhang, Xiangming; Guan, Xiying

2011-11-01

A comprehensive finite element (FE) model of the human ear including the ear canal, middle ear, and spiral cochlea was developed using histological sections of human temporal bone. The cochlea was modeled with three chambers separated by the basilar membrane and Reissner's membrane and filled with perilymphatic fluid. The viscoelastic material behavior was applied to middle ear soft tissues based on dynamic measurements of tissues in our lab. The model was validated using the experimental data obtained in human temporal bones and then used to simulate various stages of otitis media (OM) including the changes of morphology, mechanical properties, pressure, and fluid level in the middle ear. Function alterations of the middle ear and cochlea in OM were derived from the model and compared with the measurements from temporal bones. This study indicates that OM can be simulated in the FE model to predict the hearing loss induced by biomechanical changes of the middle ear and cochlea.

Fast Rotation-Free Feature-Based Image Registration Using Improved N-SIFT and GMM-Based Parallel Optimization.

Science.gov (United States)

Yu, Dongdong; Yang, Feng; Yang, Caiyun; Leng, Chengcai; Cao, Jian; Wang, Yining; Tian, Jie

2016-08-01

Image registration is a key problem in a variety of applications, such as computer vision, medical image processing, pattern recognition, etc., while the application of registration is limited by time consumption and the accuracy in the case of large pose differences. Aimed at these two kinds of problems, we propose a fast rotation-free feature-based rigid registration method based on our proposed accelerated-NSIFT and GMM registration-based parallel optimization (PO-GMMREG). Our method is accelerated by using the GPU/CUDA programming and preserving only the location information without constructing the descriptor of each interest point, while its robustness to missing correspondences and outliers is improved by converting the interest point matching to Gaussian mixture model alignment. The accuracy in the case of large pose differences is settled by our proposed PO-GMMREG algorithm by constructing a set of initial transformations. Experimental results demonstrate that our proposed algorithm can fast rigidly register 3-D medical images and is reliable for aligning 3-D scans even when they exhibit a poor initialization.

'Outrunning' the running ear

African Journals Online (AJOL)

Chantel

In even the most experienced hands, an adequate physical examination of the ears can be difficult to perform because of common problems such as cerumen blockage of the auditory canal, an unco- operative toddler or an exasperated parent. The most common cause for a running ear in a child is acute purulent otitis.

Container-code recognition system based on computer vision and deep neural networks

Science.gov (United States)

Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

2018-04-01

Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

sEMG-Based Gesture Recognition with Convolution Neural Networks

Directory of Open Access Journals (Sweden)

Zhen Ding

2018-06-01

Full Text Available The traditional classification methods for limb motion recognition based on sEMG have been deeply researched and shown promising results. However, information loss during feature extraction reduces the recognition accuracy. To obtain higher accuracy, the deep learning method was introduced. In this paper, we propose a parallel multiple-scale convolution architecture. Compared with the state-of-art methods, the proposed architecture fully considers the characteristics of the sEMG signal. Larger sizes of kernel filter than commonly used in other CNN-based hand recognition methods are adopted. Meanwhile, the characteristics of the sEMG signal, that is, muscle independence, is considered when designing the architecture. All the classification methods were evaluated on the NinaPro database. The results show that the proposed architecture has the highest recognition accuracy. Furthermore, the results indicate that parallel multiple-scale convolution architecture with larger size of kernel filter and considering muscle independence can significantly increase the classification accuracy.

Robust and Effective Component-based Banknote Recognition for the Blind.

Science.gov (United States)

Hasanuzzaman, Faiz M; Yang, Xiaodong; Tian, Yingli

2012-11-01

We develop a novel camera-based computer vision technology to automatically recognize banknotes for assisting visually impaired people. Our banknote recognition system is robust and effective with the following features: 1) high accuracy: high true recognition rate and low false recognition rate, 2) robustness: handles a variety of currency designs and bills in various conditions, 3) high efficiency: recognizes banknotes quickly, and 4) ease of use: helps blind users to aim the target for image capture. To make the system robust to a variety of conditions including occlusion, rotation, scaling, cluttered background, illumination change, viewpoint variation, and worn or wrinkled bills, we propose a component-based framework by using Speeded Up Robust Features (SURF). Furthermore, we employ the spatial relationship of matched SURF features to detect if there is a bill in the camera view. This process largely alleviates false recognition and can guide the user to correctly aim at the bill to be recognized. The robustness and generalizability of the proposed system is evaluated on a dataset including both positive images (with U.S. banknotes) and negative images (no U.S. banknotes) collected under a variety of conditions. The proposed algorithm, achieves 100% true recognition rate and 0% false recognition rate. Our banknote recognition system is also tested by blind users.

Disposal of residue from sifting of combustible waste; Avsaettning av siktrest fraan foerbehandling av braennbart avfall

Energy Technology Data Exchange (ETDEWEB)

Niklasson, Fredrik

2012-11-01

In waste to energy plants, unwanted species in the fuel may cause corrosion, deposits, agglomeration in the fuel bed, and emissions of pollutants. Countermeasures to such problems are often costly. For at least some of the waste, the fuel properties can be improved by introducing a pretreatment system in which the fine fraction is separated from the waste by sifting. This method has been studied in an earlier Waste Refinery project, WR-06. That study pointed at advantages in performance of the boiler plant and a rough economical analysis indicated substantial benefits. The drawback of the pretreatment was that the residue (the fine fraction) showed as high content of total organic carbon (TOC) as 37 %, by weight. Such a waste fraction is not allowed to be landfilled in Sweden. High TOC content is also a limiting factor for usage as a secondary construction material. To become an applicable pretreatment method, it is necessary to find an appropriate disposal method for the residue material. Present work investigates different possibilities to handle the sifting residue, assuming it has the same properties as in previous study. The residue from sifting needs further treatment, preferably with energy recovery. There are some alternatives, such as combustion, gasification, anaerobic or aerobic digestion. To reduce problems associated by combustion, the waste may be burnt in another more suitable furnace. An alternative is gasification, but that treatment method is not yet an established process for waste fuels. Another option is treatment by anaerobic or aerobic digestion. The high concentrations of metals, however, limit the use of the biologically treated waste to landfilling sites, where it may be utilized as a construction material. The high metal concentrations in the sifting residue imply that it must be kept separate from other biodegradable wastes which are used to produce fertilizers. Thus, this treatment alternative will likely require substantial new

A Robust and Efficient Algorithm for Tool Recognition and Localization for Space Station Robot

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Lingbo Cheng

2014-12-01

Full Text Available This paper studies a robust target recognition and localization method for a maintenance robot in a space station, and its main goal is to solve the target affine transformation caused by microgravity and the strong reflection and refraction of sunlight and lamplight in the cabin, as well as the occlusion of other objects. In this method, an Affine Scale Invariant Feature Transform (Affine-SIFT algorithm is proposed to extract enough local feature points with a fully affine invariant, and the stable matching point is obtained from the above point for target recognition by the selected Random Sample Consensus (RANSAC algorithm. Then, in order to localize the target, the effective and appropriate 3D grasping scope of the target is defined, and we determine and evaluate the grasping precision with the estimated affine transformation parameters presented in this paper. Finally, the threshold of RANSAC is optimized to enhance the accuracy and efficiency of target recognition and localization, and the scopes of illumination, vision distance and viewpoint angle for robot are evaluated to obtain effective image data by Root-Mean-Square Error (RMSE. An experimental system to simulate the illumination environment in a space station is established. Enough experiments have been carried out, and the experimental results show both the validity of the proposed definition of the grasping scope and the feasibility of the proposed recognition and localization method.

Finger Vein Recognition Based on Local Directional Code

Science.gov (United States)

Meng, Xianjing; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2012-01-01

Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP), Local Derivative Pattern (LDP) and Local Line Binary Pattern (LLBP). However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD), this paper represents a new direction based local descriptor called Local Directional Code (LDC) and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP. PMID:23202194

Finger Vein Recognition Based on Local Directional Code

Directory of Open Access Journals (Sweden)

Rongyang Xiao

2012-11-01

Full Text Available Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP, Local Derivative Pattern (LDP and Local Line Binary Pattern (LLBP. However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD, this paper represents a new direction based local descriptor called Local Directional Code (LDC and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP.

SAR Target Recognition Based on Multi-feature Multiple Representation Classifier Fusion

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Zhang Xinzheng

2017-10-01

Full Text Available In this paper, we present a Synthetic Aperture Radar (SAR image target recognition algorithm based on multi-feature multiple representation learning classifier fusion. First, it extracts three features from the SAR images, namely principal component analysis, wavelet transform, and Two-Dimensional Slice Zernike Moments (2DSZM features. Second, we harness the sparse representation classifier and the cooperative representation classifier with the above-mentioned features to get six predictive labels. Finally, we adopt classifier fusion to obtain the final recognition decision. We researched three different classifier fusion algorithms in our experiments, and the results demonstrate thatusing Bayesian decision fusion gives thebest recognition performance. The method based on multi-feature multiple representation learning classifier fusion integrates the discrimination of multi-features and combines the sparse and cooperative representation classification performance to gain complementary advantages and to improve recognition accuracy. The experiments are based on the Moving and Stationary Target Acquisition and Recognition (MSTAR database,and they demonstrate the effectiveness of the proposed approach.

Frame-Based Facial Expression Recognition Using Geometrical Features

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Anwar Saeed

2014-01-01

Full Text Available To improve the human-computer interaction (HCI to be as good as human-human interaction, building an efficient approach for human emotion recognition is required. These emotions could be fused from several modalities such as facial expression, hand gesture, acoustic data, and biophysiological data. In this paper, we address the frame-based perception of the universal human facial expressions (happiness, surprise, anger, disgust, fear, and sadness, with the help of several geometrical features. Unlike many other geometry-based approaches, the frame-based method does not rely on prior knowledge of a person-specific neutral expression; this knowledge is gained through human intervention and not available in real scenarios. Additionally, we provide a method to investigate the performance of the geometry-based approaches under various facial point localization errors. From an evaluation on two public benchmark datasets, we have found that using eight facial points, we can achieve the state-of-the-art recognition rate. However, this state-of-the-art geometry-based approach exploits features derived from 68 facial points and requires prior knowledge of the person-specific neutral expression. The expression recognition rate using geometrical features is adversely affected by the errors in the facial point localization, especially for the expressions with subtle facial deformations.

Robust and Effective Component-based Banknote Recognition by SURF Features.

Science.gov (United States)

Hasanuzzaman, Faiz M; Yang, Xiaodong; Tian, YingLi

2011-01-01

Camera-based computer vision technology is able to assist visually impaired people to automatically recognize banknotes. A good banknote recognition algorithm for blind or visually impaired people should have the following features: 1) 100% accuracy, and 2) robustness to various conditions in different environments and occlusions. Most existing algorithms of banknote recognition are limited to work for restricted conditions. In this paper we propose a component-based framework for banknote recognition by using Speeded Up Robust Features (SURF). The component-based framework is effective in collecting more class-specific information and robust in dealing with partial occlusion and viewpoint changes. Furthermore, the evaluation of SURF demonstrates its effectiveness in handling background noise, image rotation, scale, and illumination changes. To authenticate the robustness and generalizability of the proposed approach, we have collected a large dataset of banknotes from a variety of conditions including occlusion, cluttered background, rotation, and changes of illumination, scaling, and viewpoints. The proposed algorithm achieves 100% recognition rate on our challenging dataset.

Response procedure, memory, and dichotic emotion recognition.

Science.gov (United States)

Voyer, Daniel; Dempsey, Danielle; Harding, Jennifer A

2014-03-01

Three experiments investigated the role of memory and rehearsal in a dichotic emotion recognition task by manipulating the response procedure as well as the interval between encoding and retrieval while taking into account order of report. For all experiments, right-handed undergraduates were presented with dichotic pairs of the words bower, dower, power, and tower pronounced in a sad, angry, happy, or neutral tone of voice. Participants were asked to report the two emotions presented on each trial by clicking on the corresponding drawings or words on a computer screen, either following no delay or a five second delay. Experiment 1 applied the delay conditions as a between-subjects factor whereas it was a within-subject factor in Experiment 2. In Experiments 1 and 2, more correct responses occurred for the left than the right ear, reflecting a left ear advantage (LEA) that was slightly larger with a nonverbal than a verbal response. The LEA was also found to be larger with no delay than with the 5s delay. In addition, participants typically responded first to the left ear stimulus. In fact, the first response produced a LEA whereas the second response produced a right ear advantage. Experiment 3 involved a concurrent task during the delay to prevent rehearsal. In Experiment 3, the pattern of results supported the claim that rehearsal could account for the findings of the first two experiments. The findings are interpreted in the context of the role of rehearsal and memory in models of dichotic listening. Copyright © 2013 Elsevier Inc. All rights reserved.

Ionic diffusion and mass discrimination effects in the new generation of short flow tube SIFT-MS instruments

Czech Academy of Sciences Publication Activity Database

Smith, D.; Pysanenko, A.; Španěl, Patrik

2009-01-01

Roč. 281, 1-2 (2009), s. 15-23 ISSN 1387-3806 R&D Projects: GA ČR GA202/06/0776 Institutional research plan: CEZ:AV0Z40400503 Keywords : SIFT-MS * ionic diffusion * mass discrimination * trace gas analysis Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.117, year: 2009

Comparison of Microbiological Flora in the External Auditory Canal of Normal Ear and an Ear with Acute Otitis Externa.

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Ghanpur, Asheesh Dora; Nayak, Dipak Ranjan; Chawla, Kiran; Shashidhar, V; Singh, Rohit

2017-09-01

Acute Otitis Externa (AOE) is also known as swimmer's ear. Investigations initiated during World War II firmly established the role of bacteria in the aetiology of Acute Otitis Externa. To culture the microbiological flora of the normal ear and compare it with the flora causing AOE and to know the role of normal ear canal flora and anaerobes in the aetiology. A prospective observational study was conducted on 64 patients clinically diagnosed with unilateral AOE. Ear swabs were taken from both the ears. Microbiological flora was studied considering diseased ear as test ear and the normal ear as the control. Aerobic and anaerobic cultures were done. Severity of the disease was assessed by subjective and objective scores. Effect of topical treatment with ichthammol glycerine pack was assessed after 48 hours and scores were calculated again. Patients with scores < 4 after pack removal were started on systemic antibiotics and were assessed after seven days of antibiotics course. Data was analysed using Paired t-test, Wilcoxon signed ranks test and Chi-square test. A p-value < 0.05 was considered significant. Pseudomonas aeruginosa (33%) was the most common bacteria cultured from the ear followed by Methicillin Resistant Staphylococcus aureus (MRSA) (18%). Patients with anaerobic organism in the test ear had severe symptoms and needed systemic antibiotic therapy. Most of the cases may respond to empirical antibiotic therapy. In cases with severe symptoms and the ones refractory to empirical treatment, a culture from the ear canal will not be a tax on the patient. This helps in giving a better understanding about the disease, causative organisms and helps in avoiding the use of inappropriate antibiotics that usually result in developing resistant strains of bacteria.

Enhancing Ear and Hearing Health Access for Children With Technology and Connectivity.

Science.gov (United States)

Swanepoel, De Wet

2017-10-12

Technology and connectivity advances are demonstrating increasing potential to improve access of service delivery to persons with hearing loss. This article demonstrates use cases from community-based hearing screening and automated diagnosis of ear disease. This brief report reviews recent evidence for school- and home-based hearing testing in underserved communities using smartphone technologies paired with calibrated headphones. Another area of potential impact facilitated by technology and connectivity is the use of feature extraction algorithms to facilitate automated diagnosis of most common ear conditions from video-otoscopic images. Smartphone hearing screening using calibrated headphones demonstrated equivalent sensitivity and specificity for school-based hearing screening. Automating test sequences with a forced-choice response paradigm allowed persons with minimal training to offer screening in underserved communities. The automated image analysis and diagnosis system for ear disease demonstrated an overall accuracy of 80.6%, which is up to par and exceeds accuracy rates previously reported for general practitioners and pediatricians. The emergence of these tools that capitalize on technology and connectivity advances enables affordable and accessible models of service delivery for community-based ear and hearing care.

Quality based approach for adaptive face recognition

Science.gov (United States)

Abboud, Ali J.; Sellahewa, Harin; Jassim, Sabah A.

2009-05-01

Recent advances in biometric technology have pushed towards more robust and reliable systems. We aim to build systems that have low recognition errors and are less affected by variation in recording conditions. Recognition errors are often attributed to the usage of low quality biometric samples. Hence, there is a need to develop new intelligent techniques and strategies to automatically measure/quantify the quality of biometric image samples and if necessary restore image quality according to the need of the intended application. In this paper, we present no-reference image quality measures in the spatial domain that have impact on face recognition. The first is called symmetrical adaptive local quality index (SALQI) and the second is called middle halve (MH). Also, an adaptive strategy has been developed to select the best way to restore the image quality, called symmetrical adaptive histogram equalization (SAHE). The main benefits of using quality measures for adaptive strategy are: (1) avoidance of excessive unnecessary enhancement procedures that may cause undesired artifacts, and (2) reduced computational complexity which is essential for real time applications. We test the success of the proposed measures and adaptive approach for a wavelet-based face recognition system that uses the nearest neighborhood classifier. We shall demonstrate noticeable improvements in the performance of adaptive face recognition system over the corresponding non-adaptive scheme.

Inner ear pressure changes following square wave intracranial or ear canal pressure manipulation in the same guinea pig

NARCIS (Netherlands)

Thalen, E; Wit, H; Segenhout, H; Albers, F

Inner ear pressure was measured in scala tympani with a micropipette during square wave pressure manipulation of the intracranial compartment and, subsequently, of the external ear canal (EEC) in the same guinea pig. As expected, the combination of the cochlear aqueduct and the inner ear behaves as

Computed tomography of middle ear cholesteatomas without tympanic membrane perforation

International Nuclear Information System (INIS)

Ettorre, G.C.

1991-01-01

The growth of a middle ear cholesteatoma behind a normal tympanic membrane is a rate though possible event. In such cases, CT may provide useful information for diagnosis. The results are presented of a CT study carried out on 14 patients affected with unilateral conductive hearing loss and with normal tympanic membrane. CT allowed the diagnosis of meddle ear cholesteatoma to be made in all cases. All patients were treated with surgery: 8 of them underwent tympanoplasty and 6 explorative tympanotomy. While the diagnosis of cholesteatoma was confirmed in 13 patients, in 1 case tympanosclerosis was diagnosed. CT diagnosis of middle ear cholesteatoma is based on the demonstration of a low-density soft-tissue mass, in association with bone erosion or ossicular dislocation. The author emphasizes the difficulty of a CT diagnosis of cholesteatoma in the patients with middle ear soft-tissue masses in the absence of bone alterations

Wheat Ear Detection in Plots by Segmenting Mobile Laser Scanner Data

Science.gov (United States)

Velumani, K.; Oude Elberink, S.; Yang, M. Y.; Baret, F.

2017-09-01

The use of Light Detection and Ranging (LiDAR) to study agricultural crop traits is becoming popular. Wheat plant traits such as crop height, biomass fractions and plant population are of interest to agronomists and biologists for the assessment of a genotype's performance in the environment. Among these performance indicators, plant population in the field is still widely estimated through manual counting which is a tedious and labour intensive task. The goal of this study is to explore the suitability of LiDAR observations to automate the counting process by the individual detection of wheat ears in the agricultural field. However, this is a challenging task owing to the random cropping pattern and noisy returns present in the point cloud. The goal is achieved by first segmenting the 3D point cloud followed by the classification of segments into ears and non-ears. In this study, two segmentation techniques: a) voxel-based segmentation and b) mean shift segmentation were adapted to suit the segmentation of plant point clouds. An ear classification strategy was developed to distinguish the ear segments from leaves and stems. Finally, the ears extracted by the automatic methods were compared with reference ear segments prepared by manual segmentation. Both the methods had an average detection rate of 85 %, aggregated over different flowering stages. The voxel-based approach performed well for late flowering stages (wheat crops aged 210 days or more) with a mean percentage accuracy of 94 % and takes less than 20 seconds to process 50,000 points with an average point density of 16  points/cm2. Meanwhile, the mean shift approach showed comparatively better counting accuracy of 95% for early flowering stage (crops aged below 225 days) and takes approximately 4 minutes to process 50,000 points.

Human action recognition based on estimated weak poses

Science.gov (United States)

Gong, Wenjuan; Gonzàlez, Jordi; Roca, Francesc Xavier

2012-12-01

We present a novel method for human action recognition (HAR) based on estimated poses from image sequences. We use 3D human pose data as additional information and propose a compact human pose representation, called a weak pose, in a low-dimensional space while still keeping the most discriminative information for a given pose. With predicted poses from image features, we map the problem from image feature space to pose space, where a Bag of Poses (BOP) model is learned for the final goal of HAR. The BOP model is a modified version of the classical bag of words pipeline by building the vocabulary based on the most representative weak poses for a given action. Compared with the standard k-means clustering, our vocabulary selection criteria is proven to be more efficient and robust against the inherent challenges of action recognition. Moreover, since for action recognition the ordering of the poses is discriminative, the BOP model incorporates temporal information: in essence, groups of consecutive poses are considered together when computing the vocabulary and assignment. We tested our method on two well-known datasets: HumanEva and IXMAS, to demonstrate that weak poses aid to improve action recognition accuracies. The proposed method is scene-independent and is comparable with the state-of-art method.

Finger Vein Recognition Based on a Personalized Best Bit Map

Science.gov (United States)

Yang, Gongping; Xi, Xiaoming; Yin, Yilong

2012-01-01

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition. PMID:22438735

Average Gait Differential Image Based Human Recognition

Directory of Open Access Journals (Sweden)

Jinyan Chen

2014-01-01

Full Text Available The difference between adjacent frames of human walking contains useful information for human gait identification. Based on the previous idea a silhouettes difference based human gait recognition method named as average gait differential image (AGDI is proposed in this paper. The AGDI is generated by the accumulation of the silhouettes difference between adjacent frames. The advantage of this method lies in that as a feature image it can preserve both the kinetic and static information of walking. Comparing to gait energy image (GEI, AGDI is more fit to representation the variation of silhouettes during walking. Two-dimensional principal component analysis (2DPCA is used to extract features from the AGDI. Experiments on CASIA dataset show that AGDI has better identification and verification performance than GEI. Comparing to PCA, 2DPCA is a more efficient and less memory storage consumption feature extraction method in gait based recognition.

Intelligent fault recognition strategy based on adaptive optimized multiple centers

Science.gov (United States)

Zheng, Bo; Li, Yan-Feng; Huang, Hong-Zhong

2018-06-01

For the recognition principle based optimized single center, one important issue is that the data with nonlinear separatrix cannot be recognized accurately. In order to solve this problem, a novel recognition strategy based on adaptive optimized multiple centers is proposed in this paper. This strategy recognizes the data sets with nonlinear separatrix by the multiple centers. Meanwhile, the priority levels are introduced into the multi-objective optimization, including recognition accuracy, the quantity of optimized centers, and distance relationship. According to the characteristics of various data, the priority levels are adjusted to ensure the quantity of optimized centers adaptively and to keep the original accuracy. The proposed method is compared with other methods, including support vector machine (SVM), neural network, and Bayesian classifier. The results demonstrate that the proposed strategy has the same or even better recognition ability on different distribution characteristics of data.

Towards discrete wavelet transform-based human activity recognition

Science.gov (United States)

Khare, Manish; Jeon, Moongu

2017-06-01

Providing accurate recognition of human activities is a challenging problem for visual surveillance applications. In this paper, we present a simple and efficient algorithm for human activity recognition based on a wavelet transform. We adopt discrete wavelet transform (DWT) coefficients as a feature of human objects to obtain advantages of its multiresolution approach. The proposed method is tested on multiple levels of DWT. Experiments are carried out on different standard action datasets including KTH and i3D Post. The proposed method is compared with other state-of-the-art methods in terms of different quantitative performance measures. The proposed method is found to have better recognition accuracy in comparison to the state-of-the-art methods.

The Suitability of Cloud-Based Speech Recognition Engines for Language Learning

Science.gov (United States)

Daniels, Paul; Iwago, Koji

2017-01-01

As online automatic speech recognition (ASR) engines become more accurate and more widely implemented with call software, it becomes important to evaluate the effectiveness and the accuracy of these recognition engines using authentic speech samples. This study investigates two of the most prominent cloud-based speech recognition engines--Apple's…

Expression of macrophage migration inhibitory factor and CD74 in the inner ear and middle ear in lipopolysaccharide-induced otitis media.

Science.gov (United States)

Ishihara, Hisashi; Kariya, Shin; Okano, Mitsuhiro; Zhao, Pengfei; Maeda, Yukihide; Nishizaki, Kazunori

2016-10-01

Significant expression of macrophage migration inhibitory factor and its receptor (CD74) was observed in both the middle ear and inner ear in experimental otitis media in mice. Modulation of macrophage migration inhibitory factor and its signaling pathway might be useful in the management of inner ear inflammation due to otitis media. Inner ear dysfunction secondary to otitis media has been reported. However, the specific mechanisms involved are not clearly understood. The aim of this study is to investigate the expression of macrophage migration inhibitory factor and CD74 in the middle ear and inner ear in lipopolysaccharide-induced otitis media. BALB/c mice received a transtympanic injection of either lipopolysaccharide or phosphate-buffered saline (PBS). The mice were sacrificed 24 h after injection, and temporal bones were processed for polymerase chain reaction (PCR) analysis, histologic examination, and immunohistochemistry. PCR examination revealed that the lipopolysaccharide-injected mice showed a significant up-regulation of macrophage migration inhibitory factor in both the middle ear and inner ear as compared with the PBS-injected control mice. The immunohistochemical study showed positive reactions for macrophage migration inhibitory factor and CD74 in infiltrating inflammatory cells, middle ear mucosa, and inner ear in the lipopolysaccharide-injected mice.

Deep Belief Networks Based Toponym Recognition for Chinese Text

Directory of Open Access Journals (Sweden)

Shu Wang

2018-06-01

Full Text Available In Geographical Information Systems, geo-coding is used for the task of mapping from implicitly geo-referenced data to explicitly geo-referenced coordinates. At present, an enormous amount of implicitly geo-referenced information is hidden in unstructured text, e.g., Wikipedia, social data and news. Toponym recognition is the foundation of mining this useful geo-referenced information by identifying words as toponyms in text. In this paper, we propose an adapted toponym recognition approach based on deep belief network (DBN by exploring two key issues: word representation and model interpretation. A Skip-Gram model is used in the word representation process to represent words with contextual information that are ignored by current word representation models. We then determine the core hyper-parameters of the DBN model by illustrating the relationship between the performance and the hyper-parameters, e.g., vector dimensionality, DBN structures and probability thresholds. The experiments evaluate the performance of the Skip-Gram model implemented by the Word2Vec open-source tool, determine stable hyper-parameters and compare our approach with a conditional random field (CRF based approach. The experimental results show that the DBN model outperforms the CRF model with smaller corpus. When the corpus size is large enough, their statistical metrics become approaching. However, their recognition results express differences and complementarity on different kinds of toponyms. More importantly, combining their results can directly improve the performance of toponym recognition relative to their individual performances. It seems that the scale of the corpus has an obvious effect on the performance of toponym recognition. Generally, there is no adequate tagged corpus on specific toponym recognition tasks, especially in the era of Big Data. In conclusion, we believe that the DBN-based approach is a promising and powerful method to extract geo

Application of image recognition-based automatic hyphae detection in fungal keratitis.

Science.gov (United States)

Wu, Xuelian; Tao, Yuan; Qiu, Qingchen; Wu, Xinyi

2018-03-01

The purpose of this study is to evaluate the accuracy of two methods in diagnosis of fungal keratitis, whereby one method is automatic hyphae detection based on images recognition and the other method is corneal smear. We evaluate the sensitivity and specificity of the method in diagnosis of fungal keratitis, which is automatic hyphae detection based on image recognition. We analyze the consistency of clinical symptoms and the density of hyphae, and perform quantification using the method of automatic hyphae detection based on image recognition. In our study, 56 cases with fungal keratitis (just single eye) and 23 cases with bacterial keratitis were included. All cases underwent the routine inspection of slit lamp biomicroscopy, corneal smear examination, microorganism culture and the assessment of in vivo confocal microscopy images before starting medical treatment. Then, we recognize the hyphae images of in vivo confocal microscopy by using automatic hyphae detection based on image recognition to evaluate its sensitivity and specificity and compare with the method of corneal smear. The next step is to use the index of density to assess the severity of infection, and then find the correlation with the patients' clinical symptoms and evaluate consistency between them. The accuracy of this technology was superior to corneal smear examination (p hyphae detection of image recognition was 89.29%, and the specificity was 95.65%. The area under the ROC curve was 0.946. The correlation coefficient between the grading of the severity in the fungal keratitis by the automatic hyphae detection based on image recognition and the clinical grading is 0.87. The technology of automatic hyphae detection based on image recognition was with high sensitivity and specificity, able to identify fungal keratitis, which is better than the method of corneal smear examination. This technology has the advantages when compared with the conventional artificial identification of confocal

SIFT: A method to verify the IMRT fluence delivered during patient treatment using an electronic portal imaging device

International Nuclear Information System (INIS)

Vieira, Sandra C.; Dirkx, Maarten L.P.; Heijmen, Ben J.M.; Boer, Hans C.J. de

2004-01-01

Purpose: Radiotherapy patients are increasingly treated with intensity-modulated radiotherapy (IMRT) and high tumor doses. As part of our quality control program to ensure accurate dose delivery, a new method was investigated that enables the verification of the IMRT fluence delivered during patient treatment using an electronic portal imaging device (EPID), irrespective of changes in patient geometry. Methods and materials: Each IMRT treatment field is split into a static field and a modulated field, which are delivered in sequence. Images are acquired for both fields using an EPID. The portal dose image obtained for the static field is used to determine changes in patient geometry between the planning CT scan and the time of treatment delivery. With knowledge of these changes, the delivered IMRT fluence can be verified using the portal dose image of the modulated field. This method, called split IMRT field technique (SIFT), was validated first for several phantom geometries, followed by clinical implementation for a number of patients treated with IMRT. Results: The split IMRT field technique allows for an accurate verification of the delivered IMRT fluence (generally within 1% [standard deviation]), even if large interfraction changes in patient geometry occur. For interfraction radiological path length changes of 10 cm, deliberately introduced errors in the delivered fluence could still be detected to within 1% accuracy. Application of SIFT requires only a minor increase in treatment time relative to the standard IMRT delivery. Conclusions: A new technique to verify the delivered IMRT fluence from EPID images, which is independent of changes in the patient geometry, has been developed. SIFT has been clinically implemented for daily verification of IMRT treatment delivery

Ear replanatation: a case report and literature review

Directory of Open Access Journals (Sweden)

Krešimir Božikov

2013-10-01

Full Text Available Background: Total ear amputation is a rare accident. The most common causes are traffic accidents (33 %, followed by fights (28 %. In 1980, Pennington et al. reported the first successful microsurgical ear replantation in a 29-year old man.Methods: An English literature review of trauma cases of total ear amputation showed only 13 successful replantations with arterial and venous microanastomoses. We present a case report of successful total ear replantation with arterial and vein microanastomoses in a 17-year old boy.Results: Our ear replantation with both arterial and venous anastomoses performed was successful and we achieved an excellent aesthetic outcome.Conclusion: The reason for such a low number of successful ear replantations is technical challenge due to small vessel diameter, difficult vessel identification, vessel approach and concomitant avulsion injury. The best aesthetic result in ear reconstruction is achieved by microsurgical replantation. The surgical technique depends on the intraoperative findings. Since ear replantation is a very challenging procedure, a microsurgeon needs to discuss with the patient the risk of partial/total necrosis of the replanted ear and the possibilities of other reconstructive options.

Challenges and Specifications for Robust Face and Gait Recognition Systems for Surveillance Application

Directory of Open Access Journals (Sweden)

BUCIU Ioan

2014-05-01

Full Text Available Automated person recognition (APR based on biometric signals addresses the process of automatically recognize a person according to his physiological traits (face, voice, iris, fingerprint, ear shape, body odor, electroencephalogram – EEG, electrocardiogram, or hand geometry, or behavioural patterns (gait, signature, hand-grip, lip movement. The paper aims at briefly presenting the current challenges for two specific non-cooperative biometric approaches, namely face and gait biometrics as well as approaches that consider combination of the two in the attempt of a more robust system for accurate APR, in the context of surveillance application. Open problems from both sides are also pointed out.

Real ear unaided gain and its relation with the equivalent volume of the external and middle ear

Directory of Open Access Journals (Sweden)

Bastos, Bárbara Guimarães

2012-01-01

Full Text Available Introduction: Old age is associated with changes in the characteristics of the middle ear transmission system and in external ear resonance, and these carry implications for the hearing aid (HA verification process for which targets and measures of the real ear insertion gain (REIG are used. Aim: To compare the real ear unaided gain (REUG and the equivalent volumes of the external ear (VeqEE and the middle ear (VeqME between elderly and adult patients. Methods: This is a retrospective study in which the medical records of 28 elderly patients (aged between 61 and 102 years, average hearing thresholds between 38.75 and 85 dB HL and 23 adult patients (aged 20-59, mean hearing thresholds between 31.25 and 116.25 dB HL with bilateral sensorineural hearing loss and no history of middle ear abnormalities were analyzed. Immittance measurements (VeqEE, VeqME, and pressure of the peak of maximum compliance and the REUG (frequency and amplitude of the primary peak were recovered for a total of 40 ears. These data were compared between elderly and adults as well as between men and women, using Student's t test. Correlations (Pearson between immittance and REUG data were also verified. Results: No statistically significant differences (p < 0.01 were found for immittance and REUG data between elderly and adults, or between men and women. A negative and weak but significant correlation was observed between the REUG primary peak and VeqEE. Conclusion: Hearing aid verification can be performed with target and measures of the REIG in the elderly population.

A sensor and video based ontology for activity recognition in smart environments.

Science.gov (United States)

Mitchell, D; Morrow, Philip J; Nugent, Chris D

2014-01-01

Activity recognition is used in a wide range of applications including healthcare and security. In a smart environment activity recognition can be used to monitor and support the activities of a user. There have been a range of methods used in activity recognition including sensor-based approaches, vision-based approaches and ontological approaches. This paper presents a novel approach to activity recognition in a smart home environment which combines sensor and video data through an ontological framework. The ontology describes the relationships and interactions between activities, the user, objects, sensors and video data.

An Improved Iris Recognition Algorithm Based on Hybrid Feature and ELM

Science.gov (United States)

Wang, Juan

2018-03-01

The iris image is easily polluted by noise and uneven light. This paper proposed an improved extreme learning machine (ELM) based iris recognition algorithm with hybrid feature. 2D-Gabor filters and GLCM is employed to generate a multi-granularity hybrid feature vector. 2D-Gabor filter and GLCM feature work for capturing low-intermediate frequency and high frequency texture information, respectively. Finally, we utilize extreme learning machine for iris recognition. Experimental results reveal our proposed ELM based multi-granularity iris recognition algorithm (ELM-MGIR) has higher accuracy of 99.86%, and lower EER of 0.12% under the premise of real-time performance. The proposed ELM-MGIR algorithm outperforms other mainstream iris recognition algorithms.

Passage of albumin from the middle ear to the inner ear in otitis media in the chinchilla

International Nuclear Information System (INIS)

Goldberg, B.; Goycoolea, M.V.; Schleivert, P.M.; Shea, D.; Schachern, P.; Paparella, M.M.; Carpenter, A.M.

1981-01-01

A study of the permeability of the middle ear-inner ear interface for macromolecules was carried out in chinchillas with open and obstructed eustachian tubes utilizing tritiated human serum albumin and immunoelectrophoresis. Tritiated albumin was placed in the round window niche area or normal animals and animals in which the eustachian tubes had been obstructed for 24 hours or 14 days. The tritiated albumin was allowed to remain in the middle ear cavity for 24 hours, Samples of middle ear effusion, perilymph, blood and cerebrospinal fluid were collected and measured for radioactivity. Radioactivity was demonstrated in the perilymph. Samples of middle ear effusions and perilymph were also studied by immunoelectrophoresis with goat antihuman albumin. Albumin placed in the round window niche of an experimental animal could be recovered unchanged in the perilymph. The results suggest a pathophysiologic explanation for the association of otitis media and sensorineural hearing loss or endolymphatic hydrops

Diagnosis of hearing impairment by high resolution CT scanning of inner ear anomalies

International Nuclear Information System (INIS)

Murata, Kiyotaka; Isono, Michio; Ohta, Fumihiko

1988-01-01

High resolution CT scanning of the temporal bone in our clinic has provided a more detailed radiological classification of inner ear anomalies than before. The statistical analysis of inner ear malformations based on the theory of quantification II has produced discriminant equations for the measurable diagnosis of hearing impairment and development of the inner ear. This analysis may make it possible to diagnose total and partial deafness on ipsi- and contralateral sides. (author)

Design of a dynamic sensor inspired by bat ears

International Nuclear Information System (INIS)

Müller, Rolf; Pannala, Mittu; Praveen K Reddy, O; Meymand, Sajjad Z

2012-01-01

In bats, the outer ear shapes act as beamforming baffles that create a spatial sensitivity pattern for the reception of the biosonar signals. Whereas technical receivers for wave-based signals usually have rigid geometries, the outer ears of some bat species, such as horseshoe bats, can undergo non-rigid deformations as a result of muscular actuation. It is hypothesized that these deformations provide the animals with a mechanism to adapt their spatial hearing sensitivity on short, sub-second time scales. This biological approach could be of interest to engineering as an inspiration for the design of beamforming devices that combine flexibility with parsimonious implementation. To explore this possibility, a biomimetic dynamic baffle was designed based on a simple shape overall geometry based on an average bat ear. This shape was augmented with three different biomimetic local shape features, a ridge on its exposed surface as well as a flap and an incision along its rim. Dynamic non-rigid deformations of the shape were accomplished through a simple actuation mechanism based on linear actuation inserted at a single point. Despite its simplicity, the prototype device was able to reproduce the dynamic functional characteristics that have been predicted for its biological paragon in a qualitative fashion. (paper)

Acceleration induced water removal from ear canals.

Science.gov (United States)

Kang, Hosung; Averett, Katelee; Jung, Sunghwan

2017-11-01

Children and adults commonly experience having water trapped in the ear canals after swimming. To remove the water, individuals will shake their head sideways. Since a child's ear canal has a smaller diameter, it requires more acceleration of the head to remove the trapped water. In this study, we theoretically and experimentally investigated the acceleration required to break the surface meniscus of the water in artificial ear canals and hydrophobic-coated glass tubes. In experiments, ear canal models were 3D-printed from a CT-scanned human head. Also, glass tubes were coated with silane to match the hydrophobicity in ear canals. Then, using a linear stage, we measured the acceleration values required to forcefully eject the water from the artificial ear canals and glass tubes. A theoretical model was developed to predict the critical acceleration at a given tube diameter and water volume by using a modified Rayleigh-Taylor instability. Furthermore, this research can shed light on the potential of long-term brain injury and damage by shaking the head to push the water out of the ear canal. This research was supported by National Science Foundation Grant CBET-1604424.

Secondary iris recognition method based on local energy-orientation feature

Science.gov (United States)

Huo, Guang; Liu, Yuanning; Zhu, Xiaodong; Dong, Hongxing

2015-01-01

This paper proposes a secondary iris recognition based on local features. The application of the energy-orientation feature (EOF) by two-dimensional Gabor filter to the extraction of the iris goes before the first recognition by the threshold of similarity, which sets the whole iris database into two categories-a correctly recognized class and a class to be recognized. Therefore, the former are accepted and the latter are transformed by histogram to achieve an energy-orientation histogram feature (EOHF), which is followed by a second recognition with the chi-square distance. The experiment has proved that the proposed method, because of its higher correct recognition rate, could be designated as the most efficient and effective among its companion studies in iris recognition algorithms.

Graphic Symbol Recognition using Graph Based Signature and Bayesian Network Classifier

OpenAIRE

Luqman, Muhammad Muzzamil; Brouard, Thierry; Ramel, Jean-Yves

2010-01-01

We present a new approach for recognition of complex graphic symbols in technical documents. Graphic symbol recognition is a well known challenge in the field of document image analysis and is at heart of most graphic recognition systems. Our method uses structural approach for symbol representation and statistical classifier for symbol recognition. In our system we represent symbols by their graph based signatures: a graphic symbol is vectorized and is converted to an attributed relational g...

Effect of target-masker similarity on across-ear interference in a dichotic cocktail-party listening task.

Science.gov (United States)

Brungart, Douglas S; Simpson, Brian D

2007-09-01

Similarity between the target and masking voices is known to have a strong influence on performance in monaural and binaural selective attention tasks, but little is known about the role it might play in dichotic listening tasks with a target signal and one masking voice in the one ear and a second independent masking voice in the opposite ear. This experiment examined performance in a dichotic listening task with a target talker in one ear and same-talker, same-sex, or different-sex maskers in both the target and the unattended ears. The results indicate that listeners were most susceptible to across-ear interference with a different-sex within-ear masker and least susceptible with a same-talker within-ear masker, suggesting that the amount of across-ear interference cannot be predicted from the difficulty of selectively attending to the within-ear masking voice. The results also show that the amount of across-ear interference consistently increases when the across-ear masking voice is more similar to the target speech than the within-ear masking voice is, but that no corresponding decline in across-ear interference occurs when the across-ear voice is less similar to the target than the within-ear voice. These results are consistent with an "integrated strategy" model of speech perception where the listener chooses a segregation strategy based on the characteristics of the masker present in the target ear and the amount of across-ear interference is determined by the extent to which this strategy can also effectively be used to suppress the masker in the unattended ear.

Ear care: an update for nurses (part 1)

OpenAIRE

Millward, K.

2017-01-01

A healthy ear is vital not just for hearing, but for balance and for full engagement with the community. In the first of two articles, Kat Millward reviews the anatomy of the ear, outlines methods of dealing with cerumen, and discusses methods of assessment and diagnosis\\ud \\ud Our ears are essential for both hearing and balance. Up to 4% of the population will have difficulties with their ears relating to impacted cerumen and many of them will present in primary care with ear discomfort or h...

A Component-Based Vocabulary-Extensible Sign Language Gesture Recognition Framework

Directory of Open Access Journals (Sweden)

Shengjing Wei

2016-04-01

Full Text Available Sign language recognition (SLR can provide a helpful tool for the communication between the deaf and the external world. This paper proposed a component-based vocabulary extensible SLR framework using data from surface electromyographic (sEMG sensors, accelerometers (ACC, and gyroscopes (GYRO. In this framework, a sign word was considered to be a combination of five common sign components, including hand shape, axis, orientation, rotation, and trajectory, and sign classification was implemented based on the recognition of five components. Especially, the proposed SLR framework consisted of two major parts. The first part was to obtain the component-based form of sign gestures and establish the code table of target sign gesture set using data from a reference subject. In the second part, which was designed for new users, component classifiers were trained using a training set suggested by the reference subject and the classification of unknown gestures was performed with a code matching method. Five subjects participated in this study and recognition experiments under different size of training sets were implemented on a target gesture set consisting of 110 frequently-used Chinese Sign Language (CSL sign words. The experimental results demonstrated that the proposed framework can realize large-scale gesture set recognition with a small-scale training set. With the smallest training sets (containing about one-third gestures of the target gesture set suggested by two reference subjects, (82.6 ± 13.2% and (79.7 ± 13.4% average recognition accuracy were obtained for 110 words respectively, and the average recognition accuracy climbed up to (88 ± 13.7% and (86.3 ± 13.7% when the training set included 50~60 gestures (about half of the target gesture set. The proposed framework can significantly reduce the user’s training burden in large-scale gesture recognition, which will facilitate the implementation of a practical SLR system.

A Component-Based Vocabulary-Extensible Sign Language Gesture Recognition Framework.

Science.gov (United States)

Wei, Shengjing; Chen, Xiang; Yang, Xidong; Cao, Shuai; Zhang, Xu

2016-04-19

Sign language recognition (SLR) can provide a helpful tool for the communication between the deaf and the external world. This paper proposed a component-based vocabulary extensible SLR framework using data from surface electromyographic (sEMG) sensors, accelerometers (ACC), and gyroscopes (GYRO). In this framework, a sign word was considered to be a combination of five common sign components, including hand shape, axis, orientation, rotation, and trajectory, and sign classification was implemented based on the recognition of five components. Especially, the proposed SLR framework consisted of two major parts. The first part was to obtain the component-based form of sign gestures and establish the code table of target sign gesture set using data from a reference subject. In the second part, which was designed for new users, component classifiers were trained using a training set suggested by the reference subject and the classification of unknown gestures was performed with a code matching method. Five subjects participated in this study and recognition experiments under different size of training sets were implemented on a target gesture set consisting of 110 frequently-used Chinese Sign Language (CSL) sign words. The experimental results demonstrated that the proposed framework can realize large-scale gesture set recognition with a small-scale training set. With the smallest training sets (containing about one-third gestures of the target gesture set) suggested by two reference subjects, (82.6 ± 13.2)% and (79.7 ± 13.4)% average recognition accuracy were obtained for 110 words respectively, and the average recognition accuracy climbed up to (88 ± 13.7)% and (86.3 ± 13.7)% when the training set included 50~60 gestures (about half of the target gesture set). The proposed framework can significantly reduce the user's training burden in large-scale gesture recognition, which will facilitate the implementation of a practical SLR system.

Incorporating anthropometry into design of ear-related products.

Science.gov (United States)

Liu, Bor-Shong

2008-01-01

To achieve mass customization and collaborative product design, human factors and ergonomics should play a key development role. The purpose of this study was to provide product designers with the anthropometic dimensions of outer ears for different demographic data, including gender and age. The second purpose was to compare the dimensions of various ear-related products (i.e., earphone, bluetooth earphone and ear-cup earphone) with the anthropometic database and recommend appropriate solutions for design. Two hundred subjects aged 20-59 was selected for this study and divided into four age stratifications. Further, three different dimensions of the outer ear (i.e., the earhole length, the ear connection length and the length of the pinna) were measured by superimposed grid photographic technique. The analysis of variance (ANOVA) was used to investigate the effects of gender, and age on ear dimensions. The results showed that all ear dimensions had significant gender effects. A comparison between the anthropometric dimensions and those of current products revealed that most current ear-related products need to be redesigned using anthropometric data. The shapes of earhole and pinna are not circular. Consequently, ear products need to be elongated so that users may feel more comfortably and not have the product slip off easily.

Face-based recognition techniques: proposals for the metrological characterization of global and feature-based approaches

Science.gov (United States)

Betta, G.; Capriglione, D.; Crenna, F.; Rossi, G. B.; Gasparetto, M.; Zappa, E.; Liguori, C.; Paolillo, A.

2011-12-01

Security systems based on face recognition through video surveillance systems deserve great interest. Their use is important in several areas including airport security, identification of individuals and access control to critical areas. These systems are based either on the measurement of details of a human face or on a global approach whereby faces are considered as a whole. The recognition is then performed by comparing the measured parameters with reference values stored in a database. The result of this comparison is not deterministic because measurement results are affected by uncertainty due to random variations and/or to systematic effects. In these circumstances the recognition of a face is subject to the risk of a faulty decision. Therefore, a proper metrological characterization is needed to improve the performance of such systems. Suitable methods are proposed for a quantitative metrological characterization of face measurement systems, on which recognition procedures are based. The proposed methods are applied to three different algorithms based either on linear discrimination, on eigenface analysis, or on feature detection.

Face-based recognition techniques: proposals for the metrological characterization of global and feature-based approaches

International Nuclear Information System (INIS)

Betta, G; Capriglione, D; Crenna, F; Rossi, G B; Gasparetto, M; Zappa, E; Liguori, C; Paolillo, A

2011-01-01

Security systems based on face recognition through video surveillance systems deserve great interest. Their use is important in several areas including airport security, identification of individuals and access control to critical areas. These systems are based either on the measurement of details of a human face or on a global approach whereby faces are considered as a whole. The recognition is then performed by comparing the measured parameters with reference values stored in a database. The result of this comparison is not deterministic because measurement results are affected by uncertainty due to random variations and/or to systematic effects. In these circumstances the recognition of a face is subject to the risk of a faulty decision. Therefore, a proper metrological characterization is needed to improve the performance of such systems. Suitable methods are proposed for a quantitative metrological characterization of face measurement systems, on which recognition procedures are based. The proposed methods are applied to three different algorithms based either on linear discrimination, on eigenface analysis, or on feature detection

Adaptive Self-Occlusion Behavior Recognition Based on pLSA

Directory of Open Access Journals (Sweden)

Hong-bin Tu

2013-01-01

Full Text Available Human action recognition is an important area of human action recognition research. Focusing on the problem of self-occlusion in the field of human action recognition, a new adaptive occlusion state behavior recognition approach was presented based on Markov random field and probabilistic Latent Semantic Analysis (pLSA. Firstly, the Markov random field was used to represent the occlusion relationship between human body parts in terms an occlusion state variable by phase space obtained. Then, we proposed a hierarchical area variety model. Finally, we use the topic model of pLSA to recognize the human behavior. Experiments were performed on the KTH, Weizmann, and Humaneva dataset to test and evaluate the proposed method. The compared experiment results showed that what the proposed method can achieve was more effective than the compared methods.

Recognition of online handwritten Gurmukhi characters based on ...

Indian Academy of Sciences (India)

Karun Verma

as the recognition of characters using rule based post-pro- cessing algorithm. ... ods in their work in order to recognize handwriting with pen-based devices. ..... Centernew is the average y-coordinate value of new stroke and denotes the center ...

Isoprene levels in the exhaled breath of 200 healthy pupils within the age range 7-18 years studied using SIFT-MS

Czech Academy of Sciences Publication Activity Database

Smith, D.; Španěl, Patrik; Enderby, B.; Lenney, W.; Turner, C.; Davies, S. J.

2010-01-01

Roč. 4, č. 1 (2010), 017101 ISSN 1752-7155 Institutional research plan: CEZ:AV0Z40400503 Keywords : SIFT-MS * mass spectroscopy * isoprene Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.828, year: 2010

Vision-Based Navigation and Recognition

National Research Council Canada - National Science Library

Rosenfeld, Azriel

1998-01-01

.... (4) Invariants: both geometric and other types. (5) Human faces: Analysis of images of human faces, including feature extraction, face recognition, compression, and recognition of facial expressions...

Vision-Based Navigation and Recognition

National Research Council Canada - National Science Library

Rosenfeld, Azriel

1996-01-01

.... (4) Invariants -- both geometric and other types. (5) Human faces: Analysis of images of human faces, including feature extraction, face recognition, compression, and recognition of facial expressions...

Objective Audiometry using Ear-EEG

DEFF Research Database (Denmark)

Christensen, Christian Bech; Kidmose, Preben

Recently, a novel electroencephalographic (EEG) method called ear-EEG [1], that enable recording of auditory evoked potentials (AEPs) from a personalized earpiece was introduced. Initial investigations show that well established AEPs, such as ASSR and P1-N1-P2 complex can be observed from ear-EEG...

FT-IR Microspectroscopy of Rat Ear Cartilage.

Directory of Open Access Journals (Sweden)

Benedicto de Campos Vidal

Full Text Available Rat ear cartilage was studied using Fourier transform-infrared (FT-IR microspectroscopy to expand the current knowledge which has been established for relatively more complex cartilage types. Comparison of the FT-IR spectra of the ear cartilage extracellular matrix (ECM with published data on articular cartilage, collagen II and 4-chondroitin-sulfate standards, as well as of collagen type I-containing dermal collagen bundles (CBs with collagen type II, was performed. Ear cartilage ECM glycosaminoglycans (GAGs were revealed histochemically and as a reduction in ECM FT-IR spectral band heights (1140-820 cm-1 after testicular hyaluronidase digestion. Although ear cartilage is less complex than articular cartilage, it contains ECM components with a macromolecular orientation as revealed using polarization microscopy. Collagen type II and GAGs, which play a structural role in the stereo-arrangement of the ear cartilage, contribute to its FT-IR spectrum. Similar to articular cartilage, ear cartilage showed that proteoglycans add a contribution to the collagen amide I spectral region, a finding that does not recommend this region for collagen type II quantification purposes. In contrast to articular cartilage, the symmetric stretching vibration of -SO3- groups at 1064 cm-1 appeared under-represented in the FT-IR spectral profile of ear cartilage. Because the band corresponding to the asymmetric stretching vibration of -SO3- groups (1236-1225 cm-1 overlapped with that of amide III bands, it is not recommended for evaluation of the -SO3- contribution to the FT-IR spectrum of the ear cartilage ECM. Instead, a peak (or shoulder at 1027-1016 cm-1 could be better considered for this intent. Amide I/amide II ratios as calculated here and data from the literature suggest that protein complexes of the ear cartilage ECM are arranged with a lower helical conformation compared to pure collagen II. The present results could motivate further studies on this tissue

Internally Coupled Ears in Living Mammals

OpenAIRE

Mason, Matthew James

2015-01-01

It is generally held that the right and left middle ears of mammals are acoustically isolated from each other, such that mammals must rely on neural computation to derive sound localisation cues. There are, however, some unusual species in which the middle ear cavities intercommunicate, in which case each ear might be able to act as a pressure-difference receiver. This could improve sound localisation at lower frequencies. The platypus Ornithorhynchus is apparently unique among mammals in tha...

A metabolic fingerprinting approach based on selected ion flow tube mass spectrometry (SIFT-MS) and chemometrics: A reliable tool for Mediterranean origin-labeled olive oils authentication.

Science.gov (United States)

Bajoub, Aadil; Medina-Rodríguez, Santiago; Ajal, El Amine; Cuadros-Rodríguez, Luis; Monasterio, Romina Paula; Vercammen, Joeri; Fernández-Gutiérrez, Alberto; Carrasco-Pancorbo, Alegría

2018-04-01

Selected Ion flow tube mass spectrometry (SIFT-MS) in combination with chemometrics was used to authenticate the geographical origin of Mediterranean virgin olive oils (VOOs) produced under geographical origin labels. In particular, 130 oil samples from six different Mediterranean regions (Kalamata (Greece); Toscana (Italy); Meknès and Tyout (Morocco); and Priego de Córdoba and Baena (Spain)) were considered. The headspace volatile fingerprints were measured by SIFT-MS in full scan with H 3 O + , NO + and O 2 + as precursor ions and the results were subjected to chemometric treatments. Principal Component Analysis (PCA) was used for preliminary multivariate data analysis and Partial Least Squares-Discriminant Analysis (PLS-DA) was applied to build different models (considering the three reagent ions) to classify samples according to the country of origin and regions (within the same country). The multi-class PLS-DA models showed very good performance in terms of fitting accuracy (98.90-100%) and prediction accuracy (96.70-100% accuracy for cross validation and 97.30-100% accuracy for external validation (test set)). Considering the two-class PLS-DA models, the one for the Spanish samples showed 100% sensitivity, specificity and accuracy in calibration, cross validation and external validation; the model for Moroccan oils also showed very satisfactory results (with perfect scores for almost every parameter in all the cases). Copyright © 2017 Elsevier Ltd. All rights reserved.

Movement of the external ear in human embryo.

Science.gov (United States)

Kagurasho, Miho; Yamada, Shigehito; Uwabe, Chigako; Kose, Katsumi; Takakuwa, Tetsuya

2012-02-01

External ears, one of the major face components, show an interesting movement during craniofacial morphogenesis in human embryo. The present study was performed to see if movement of the external ears in a human embryo could be explained by differential growth. In all, 171 samples between Carnegie stage (CS) 17 and CS 23 were selected from MR image datasets of human embryos obtained from the Kyoto Collection of Human Embryos. The three-dimensional absolute position of 13 representative anatomical landmarks, including external and internal ears, from MRI data was traced to evaluate the movement between the different stages with identical magnification. Two different sets of reference axes were selected for evaluation and comparison of the movements. When the pituitary gland and the first cervical vertebra were selected as a reference axis, the 13 anatomical landmarks of the face spread out within the same region as the embryo enlarged and changed shape. The external ear did move mainly laterally, but not cranially. The distance between the external and internal ear stayed approximately constant. Three-dimensionally, the external ear located in the caudal ventral parts of the internal ear in CS 17, moved mainly laterally until CS 23. When surface landmarks eyes and mouth were selected as a reference axis, external ears moved from the caudal lateral ventral region to the position between eyes and mouth during development. The results indicate that movement of all anatomical landmarks, including external and internal ears, can be explained by differential growth. Also, when the external ear is recognized as one of the facial landmarks and having a relative position to other landmarks such as the eyes and mouth, the external ears seem to move cranially. © 2012 Kagurasho et al; licensee BioMed Central Ltd.

ANALYTIC WORD RECOGNITION WITHOUT SEGMENTATION BASED ON MARKOV RANDOM FIELDS

NARCIS (Netherlands)

Coisy, C.; Belaid, A.

2004-01-01

In this paper, a method for analytic handwritten word recognition based on causal Markov random fields is described. The words models are HMMs where each state corresponds to a letter; each letter is modelled by a NSHP­HMM (Markov field). Global models are build dynamically, and used for recognition

Molecular Recognition: Detection of Colorless Compounds Based on Color Change

Science.gov (United States)

Khalafi, Lida; Kashani, Samira; Karimi, Javad

2016-01-01

A laboratory experiment is described in which students measure the amount of cetirizine in allergy-treatment tablets based on molecular recognition. The basis of recognition is competition of cetirizine with phenolphthalein to form an inclusion complex with ß-cyclodextrin. Phenolphthalein is pinkish under basic condition, whereas it's complex form…

Human Gait Recognition Based on Multiview Gait Sequences

Directory of Open Access Journals (Sweden)

Xiaxi Huang

2008-05-01

Full Text Available Most of the existing gait recognition methods rely on a single view, usually the side view, of the walking person. This paper investigates the case in which several views are available for gait recognition. It is shown that each view has unequal discrimination power and, therefore, should have unequal contribution in the recognition process. In order to exploit the availability of multiple views, several methods for the combination of the results that are obtained from the individual views are tested and evaluated. A novel approach for the combination of the results from several views is also proposed based on the relative importance of each view. The proposed approach generates superior results, compared to those obtained by using individual views or by using multiple views that are combined using other combination methods.

A recurrent dynamic model for correspondence-based face recognition.

Science.gov (United States)

Wolfrum, Philipp; Wolff, Christian; Lücke, Jörg; von der Malsburg, Christoph

2008-12-29

Our aim here is to create a fully neural, functionally competitive, and correspondence-based model for invariant face recognition. By recurrently integrating information about feature similarities, spatial feature relations, and facial structure stored in memory, the system evaluates face identity ("what"-information) and face position ("where"-information) using explicit representations for both. The network consists of three functional layers of processing, (1) an input layer for image representation, (2) a middle layer for recurrent information integration, and (3) a gallery layer for memory storage. Each layer consists of cortical columns as functional building blocks that are modeled in accordance with recent experimental findings. In numerical simulations we apply the system to standard benchmark databases for face recognition. We find that recognition rates of our biologically inspired approach lie in the same range as recognition rates of recent and purely functionally motivated systems.

Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature

Directory of Open Access Journals (Sweden)

Shouyi Yin

2015-01-01

Full Text Available Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed.

Infrared face recognition based on LBP histogram and KW feature selection

Science.gov (United States)

Xie, Zhihua

2014-07-01

The conventional LBP-based feature as represented by the local binary pattern (LBP) histogram still has room for performance improvements. This paper focuses on the dimension reduction of LBP micro-patterns and proposes an improved infrared face recognition method based on LBP histogram representation. To extract the local robust features in infrared face images, LBP is chosen to get the composition of micro-patterns of sub-blocks. Based on statistical test theory, Kruskal-Wallis (KW) feature selection method is proposed to get the LBP patterns which are suitable for infrared face recognition. The experimental results show combination of LBP and KW features selection improves the performance of infrared face recognition, the proposed method outperforms the traditional methods based on LBP histogram, discrete cosine transform(DCT) or principal component analysis(PCA).

On the Keyhole Hypothesis: High Mutual Information between Ear and Scalp EEG

Directory of Open Access Journals (Sweden)

Kaare B. Mikkelsen

2017-06-01

Full Text Available We propose and test the keyhole hypothesis—that measurements from low dimensional EEG, such as ear-EEG reflect a broadly distributed set of neural processes. We formulate the keyhole hypothesis in information theoretical terms. The experimental investigation is based on legacy data consisting of 10 subjects exposed to a battery of stimuli, including alpha-attenuation, auditory onset, and mismatch-negativity responses and a new medium-long EEG experiment involving data acquisition during 13 h. Linear models were estimated to lower bound the scalp-to-ear capacity, i.e., predicting ear-EEG data from simultaneously recorded scalp EEG. A cross-validation procedure was employed to ensure unbiased estimates. We present several pieces of evidence in support of the keyhole hypothesis: There is a high mutual information between data acquired at scalp electrodes and through the ear-EEG “keyhole,” furthermore we show that the view—represented as a linear mapping—is stable across both time and mental states. Specifically, we find that ear-EEG data can be predicted reliably from scalp EEG. We also address the reverse view, and demonstrate that large portions of the scalp EEG can be predicted from ear-EEG, with the highest predictability achieved in the temporal regions and when using ear-EEG electrodes with a common reference electrode.

Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression.

Directory of Open Access Journals (Sweden)

Guangwei Gao

Full Text Available In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous occlusions. However, the recognition performance of nuclear norm-based matrix regression degrades greatly in the face of the small sample size problem. An alternative solution to tackle this problem is performing matrix regression on each patch and then integrating the outputs from all patches. However, it is difficult to set an optimal patch size across different databases. To fully utilize the complementary information from different patch scales for the final decision, we propose a multi-scale patch-based matrix regression scheme based on which the ensemble of multi-scale outputs can be achieved optimally. Extensive experiments on benchmark face databases validate the effectiveness and robustness of our method, which outperforms several state-of-the-art patch-based face recognition algorithms.

Iris double recognition based on modified evolutionary neural network

Science.gov (United States)

Liu, Shuai; Liu, Yuan-Ning; Zhu, Xiao-Dong; Huo, Guang; Liu, Wen-Tao; Feng, Jia-Kai

2017-11-01

Aiming at multicategory iris recognition under illumination and noise interference, this paper proposes a method of iris double recognition based on a modified evolutionary neural network. An equalization histogram and Laplace of Gaussian operator are used to process the iris to suppress illumination and noise interference and Haar wavelet to convert the iris feature to binary feature encoding. Calculate the Hamming distance for the test iris and template iris , and compare with classification threshold, determine the type of iris. If the iris cannot be identified as a different type, there needs to be a secondary recognition. The connection weights in back-propagation (BP) neural network use modified evolutionary neural network to adaptively train. The modified neural network is composed of particle swarm optimization with mutation operator and BP neural network. According to different iris libraries in different circumstances of experimental results, under illumination and noise interference, the correct recognition rate of this algorithm is higher, the ROC curve is closer to the coordinate axis, the training and recognition time is shorter, and the stability and the robustness are better.

Model-based recognition of 3-D objects by geometric hashing technique

International Nuclear Information System (INIS)

Severcan, M.; Uzunalioglu, H.

1992-09-01

A model-based object recognition system is developed for recognition of polyhedral objects. The system consists of feature extraction, modelling and matching stages. Linear features are used for object descriptions. Lines are obtained from edges using rotation transform. For modelling and recognition process, geometric hashing method is utilized. Each object is modelled using 2-D views taken from the viewpoints on the viewing sphere. A hidden line elimination algorithm is used to find these views from the wire frame model of the objects. The recognition experiments yielded satisfactory results. (author). 8 refs, 5 figs

A Full-Body Layered Deformable Model for Automatic Model-Based Gait Recognition

Science.gov (United States)

Lu, Haiping; Plataniotis, Konstantinos N.; Venetsanopoulos, Anastasios N.

2007-12-01

This paper proposes a full-body layered deformable model (LDM) inspired by manually labeled silhouettes for automatic model-based gait recognition from part-level gait dynamics in monocular video sequences. The LDM is defined for the fronto-parallel gait with 22 parameters describing the human body part shapes (widths and lengths) and dynamics (positions and orientations). There are four layers in the LDM and the limbs are deformable. Algorithms for LDM-based human body pose recovery are then developed to estimate the LDM parameters from both manually labeled and automatically extracted silhouettes, where the automatic silhouette extraction is through a coarse-to-fine localization and extraction procedure. The estimated LDM parameters are used for model-based gait recognition by employing the dynamic time warping for matching and adopting the combination scheme in AdaBoost.M2. While the existing model-based gait recognition approaches focus primarily on the lower limbs, the estimated LDM parameters enable us to study full-body model-based gait recognition by utilizing the dynamics of the upper limbs, the shoulders and the head as well. In the experiments, the LDM-based gait recognition is tested on gait sequences with differences in shoe-type, surface, carrying condition and time. The results demonstrate that the recognition performance benefits from not only the lower limb dynamics, but also the dynamics of the upper limbs, the shoulders and the head. In addition, the LDM can serve as an analysis tool for studying factors affecting the gait under various conditions.

Anthropometric growth study of the ear in a Chinese population.

Science.gov (United States)

Zhao, Shichun; Li, Dianguo; Liu, Zhenzhong; Wang, Yibiao; Liu, Lei; Jiang, Duyin; Pan, Bo

2018-04-01

A large number of anthropometric studies of the auricle have been reported in different nations, but little data were available in the Chinese population. The aim of this study was to analyze growth changes in the ear by measuring the width and length of ears in a Chinese population. A total of 480 participants were enrolled and classified into 1-, 3-, 5-, 7-, 9-, 12-, 14-, and 18-year groups (half were boys and half were girls in each group). Ear length, ear width, body weight, and body length were measured and recorded; ear index was calculated according to ear length and ear width. The growth of auricle and differences between genders were analyzed. Growth of ear in relation to body height and weight and the degree of emphasis on the length and width of the auricle were also analyzed. Ear length and width increased with age. Ear length achieved its mature size in both 14-year-old males and females. Ear width reached its mature size in males at 7 years and in females at 5 years. Different trends of ear index were shown between males and females. People in this population paid more attention to the length than the width of the auricle. The data indicated that ear development followed increase in age. There were gender and ethnic difference in the development of ear. These results may have potential implications for the diagnosis of congenital malformations, syndromes, and planning of ear reconstruction surgery. Copyright © 2017 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Temporal bone CT analysis of congenital ear anomalies

International Nuclear Information System (INIS)

Hwang, Jung Won; Moon, Min Joo; Sung, Kyu Bo

1988-01-01

Authors analysed the CT findings of the congenital ear anomalies of twenty-nine patients for 2 years and 3 months. The results were as follows: 1. Most of the patients were under the age of 20 (82.7%) and prevalent in male (72.4%). 2. Clinically, congenital ear anomalies were detected in 20 patients (68.9%), conductive hearing loss in 4, sensorineural hearing loss in 1, and the remained 4 patients were detected incidentally without clinical symptom. 3. In the cases of unilateral involvement of 20 patients, right ear was more common (12/20). Eight of 9 bilateral involvement showed similar degree. 4. The middle ear malformations were found in 22 patients (75.9%) and bilateral in 4 patients. 26 cases of middle ear malformations had been classified by Frey into 4 groups; Group I in 5, Group II in 9, Graoup III in 9 and Group IV in 3. 5. Incidentally found ear anomaly was lateral semicircular canal formed a single cavity with the vestibule in all patients (5 pts.). 6. Inner ear malformations accompanying sensorineural hearing loss were found in 3 patients with bilateral involvement and middle ear malformations were accompanied in 2 patients. The degree of involvement of labyrinth was variable.

Insights into inner ear-specific gene regulation: epigenetics and non-coding RNAs in inner ear development and regeneration

Science.gov (United States)

Avraham, Karen B.

2016-01-01

The vertebrate inner ear houses highly specialized sensory organs, tuned to detect and encode sound, head motion and gravity. Gene expression programs under the control of transcription factors orchestrate the formation and specialization of the non-sensory inner ear labyrinth and its sensory constituents. More recently, epigenetic factors and non-coding RNAs emerged as an additional layer of gene regulation, both in inner ear development and disease. In this review, we provide an overview on how epigenetic modifications and non-coding RNAs, in particular microRNAs (miRNAs), influence gene expression and summarize recent discoveries that highlight their critical role in the proper formation of the inner ear labyrinth and its sensory organs. In contrast to non-mammalian vertebrates, adult mammals lack the ability to regenerate inner ear mechano-sensory hair cells. Finally, we discuss recent insights into how epigenetic factors and miRNAs may facilitate, or in the case of mammals, restrict sensory hair cell regeneration. PMID:27836639

Eyes and ears: Using eye tracking and pupillometry to understand challenges to speech recognition.

Science.gov (United States)

Van Engen, Kristin J; McLaughlin, Drew J

2018-05-04

Although human speech recognition is often experienced as relatively effortless, a number of common challenges can render the task more difficult. Such challenges may originate in talkers (e.g., unfamiliar accents, varying speech styles), the environment (e.g. noise), or in listeners themselves (e.g., hearing loss, aging, different native language backgrounds). Each of these challenges can reduce the intelligibility of spoken language, but even when intelligibility remains high, they can place greater processing demands on listeners. Noisy conditions, for example, can lead to poorer recall for speech, even when it has been correctly understood. Speech intelligibility measures, memory tasks, and subjective reports of listener difficulty all provide critical information about the effects of such challenges on speech recognition. Eye tracking and pupillometry complement these methods by providing objective physiological measures of online cognitive processing during listening. Eye tracking records the moment-to-moment direction of listeners' visual attention, which is closely time-locked to unfolding speech signals, and pupillometry measures the moment-to-moment size of listeners' pupils, which dilate in response to increased cognitive load. In this paper, we review the uses of these two methods for studying challenges to speech recognition. Copyright © 2018. Published by Elsevier B.V.

Multislice spiral computed tomography imaging in congenital inner ear malformations.

Science.gov (United States)

Ma, Hui; Han, Ping; Liang, Bo; Tian, Zhi-liang; Lei, Zi-qiao; Kong, Wei-jia; Feng, Gan-sheng

2008-01-01

The purpose of this study is to evaluate the usefulness of multislice spiral computed tomography (CT) in the diagnosis of congenital inner ear malformations. Forty-four patients with sensorineural hearing loss were examined on a Somatom Sensation 16 (Siemens) CT scanner. The 3-dimensional reconstructions and multiplanar reformation (MPR) were performed using the volume-rendering technique (VRT) on the workstation. Of the 44 patients examined for this study, 25 patients were found to be normal and 19 patients (36 ears) were diagnosed with congenital inner ear malformations. Of the malformations, the axial, MPR, and VRT images can all display the site and degree in 33 of the ears. Volume-rendering technique images were superior to the axial images in displaying the malformations in 3 ears with small lateral semicircular canal malformations. The common malformations were Michel deformity (1 ear), common cavity deformity (3 ears), incomplete partition I (3 ears), incomplete partition II (Mondini deformity) (5 ears), vestibular and semicircular canal malformations (14 ears), enlarged vestibular aqueduct (16 ears, 6 of which had other malformations), and internal auditory canal malformation (8 ears, all accompanied by other malformations). Multislice spiral CT allows a comprehensively assessment of various congenital inner ear malformations through high-quality MPR and VRT reconstructions. Volume-rendering technique images can display the site and degree of the malformation 3-dimensionally and intuitionisticly. This is very useful to the cochlear implantation.

Enhanced iris recognition method based on multi-unit iris images

Science.gov (United States)

Shin, Kwang Yong; Kim, Yeong Gon; Park, Kang Ryoung

2013-04-01

For the purpose of biometric person identification, iris recognition uses the unique characteristics of the patterns of the iris; that is, the eye region between the pupil and the sclera. When obtaining an iris image, the iris's image is frequently rotated because of the user's head roll toward the left or right shoulder. As the rotation of the iris image leads to circular shifting of the iris features, the accuracy of iris recognition is degraded. To solve this problem, conventional iris recognition methods use shifting of the iris feature codes to perform the matching. However, this increases the computational complexity and level of false acceptance error. To solve these problems, we propose a novel iris recognition method based on multi-unit iris images. Our method is novel in the following five ways compared with previous methods. First, to detect both eyes, we use Adaboost and a rapid eye detector (RED) based on the iris shape feature and integral imaging. Both eyes are detected using RED in the approximate candidate region that consists of the binocular region, which is determined by the Adaboost detector. Second, we classify the detected eyes into the left and right eyes, because the iris patterns in the left and right eyes in the same person are different, and they are therefore considered as different classes. We can improve the accuracy of iris recognition using this pre-classification of the left and right eyes. Third, by measuring the angle of head roll using the two center positions of the left and right pupils, detected by two circular edge detectors, we obtain the information of the iris rotation angle. Fourth, in order to reduce the error and processing time of iris recognition, adaptive bit-shifting based on the measured iris rotation angle is used in feature matching. Fifth, the recognition accuracy is enhanced by the score fusion of the left and right irises. Experimental results on the iris open database of low-resolution images showed that the

Utilization-based object recognition in confined spaces

Science.gov (United States)

Shirkhodaie, Amir; Telagamsetti, Durga; Chan, Alex L.

2017-05-01

Recognizing substantially occluded objects in confined spaces is a very challenging problem for ground-based persistent surveillance systems. In this paper, we discuss the ontology inference of occluded object recognition in the context of in-vehicle group activities (IVGA) and describe an approach that we refer to as utilization-based object recognition method. We examine the performance of three types of classifiers tailored for the recognition of objects with partial visibility, namely, (1) Hausdorff Distance classifier, (2) Hamming Network classifier, and (3) Recurrent Neural Network classifier. In order to train these classifiers, we have generated multiple imagery datasets containing a mixture of common objects appearing inside a vehicle with full or partial visibility and occultation. To generate dynamic interactions between multiple people, we model the IVGA scenarios using a virtual simulation environment, in which a number of simulated actors perform a variety of IVGA tasks independently or jointly. This virtual simulation engine produces the much needed imagery datasets for the verification and validation of the efficiency and effectiveness of the selected object recognizers. Finally, we improve the performance of these object recognizers by incorporating human gestural information that differentiates various object utilization or handling methods through the analyses of dynamic human-object interactions (HOI), human-human interactions (HHI), and human-vehicle interactions (HVI) in the context of IVGA.

Cough Recognition Based on Mel Frequency Cepstral Coefficients and Dynamic Time Warping

Science.gov (United States)

Zhu, Chunmei; Liu, Baojun; Li, Ping

Cough recognition provides important clinical information for the treatment of many respiratory diseases, but the assessment of cough frequency over a long period of time remains unsatisfied for either clinical or research purpose. In this paper, according to the advantage of dynamic time warping (DTW) and the characteristic of cough recognition, an attempt is made to adapt DTW as the recognition algorithm for cough recognition. The process of cough recognition based on mel frequency cepstral coefficients (MFCC) and DTW is introduced. Experiment results of testing samples from 3 subjects show that acceptable performances of cough recognition are obtained by DTW with a small training set.

Finding Objects for Assisting Blind People.

Science.gov (United States)

Yi, Chucai; Flores, Roberto W; Chincha, Ricardo; Tian, Yingli

2013-07-01

Computer vision technology has been widely used for blind assistance, such as navigation and wayfinding. However, few camera-based systems are developed for helping blind or visually-impaired people to find daily necessities. In this paper, we propose a prototype system of blind-assistant object finding by camera-based network and matching-based recognition. We collect a dataset of daily necessities and apply Speeded-Up Robust Features (SURF) and Scale Invariant Feature Transform (SIFT) feature descriptors to perform object recognition. Experimental results demonstrate the effectiveness of our prototype system.

Convolutional Neural Network-Based Finger-Vein Recognition Using NIR Image Sensors.

Science.gov (United States)

Hong, Hyung Gil; Lee, Min Beom; Park, Kang Ryoung

2017-06-06

Conventional finger-vein recognition systems perform recognition based on the finger-vein lines extracted from the input images or image enhancement, and texture feature extraction from the finger-vein images. In these cases, however, the inaccurate detection of finger-vein lines lowers the recognition accuracy. In the case of texture feature extraction, the developer must experimentally decide on a form of the optimal filter for extraction considering the characteristics of the image database. To address this problem, this research proposes a finger-vein recognition method that is robust to various database types and environmental changes based on the convolutional neural network (CNN). In the experiments using the two finger-vein databases constructed in this research and the SDUMLA-HMT finger-vein database, which is an open database, the method proposed in this research showed a better performance compared to the conventional methods.

Digital Active Noise Reduction Ear Plugs

National Research Council Canada - National Science Library

Harley, Thomas

1994-01-01

.... In contrast to available ANR headsets that implement fixed analog filters, the prototype defines a digital filter that is optimally defined for the user's current acoustical environment. An above-the-ear (ATE) and an in-the-ear (ITE...

Middle ear infection (otitis media) (image)

Science.gov (United States)

Otitis media is an inflammation or infection of the middle ear. Acute otitis media (acute ear infection) occurs when there is ... which causes production of fluid or pus. Chronic otitis media occurs when the eustachian tube becomes blocked ...

Multi-Layer Sparse Representation for Weighted LBP-Patches Based Facial Expression Recognition

Directory of Open Access Journals (Sweden)

Qi Jia

2015-03-01

Full Text Available In this paper, a novel facial expression recognition method based on sparse representation is proposed. Most contemporary facial expression recognition systems suffer from limited ability to handle image nuisances such as low resolution and noise. Especially for low intensity expression, most of the existing training methods have quite low recognition rates. Motivated by sparse representation, the problem can be solved by finding sparse coefficients of the test image by the whole training set. Deriving an effective facial representation from original face images is a vital step for successful facial expression recognition. We evaluate facial representation based on weighted local binary patterns, and Fisher separation criterion is used to calculate the weighs of patches. A multi-layer sparse representation framework is proposed for multi-intensity facial expression recognition, especially for low-intensity expressions and noisy expressions in reality, which is a critical problem but seldom addressed in the existing works. To this end, several experiments based on low-resolution and multi-intensity expressions are carried out. Promising results on publicly available databases demonstrate the potential of the proposed approach.

Ear Disorders in Scuba Divers

Directory of Open Access Journals (Sweden)

MH Azizi

2010-12-01

Full Text Available History of underwater diving dates back to antiquity. Breath-hold technique in diving was known to the ancient nations. However, deep diving progressed only in the early decades of the 19th century as the result of advancements in efficient underwater technologies which subsequently led to invention of sophisticated sets of scuba diving in the 20th century. Currently, diving is performed for various purposes including commercial, recreational, military, underwater construction, oil industry, underwater archeology and scientific assessment of marine life. By increasing popularity of underwater diving, dive-related medical conditions gradually became more evident and created a new challenge for the health care professionals, so that eventually, a specialty the so-called “diving medicine” was established. Most of the diving-associated disorders appear in the head and neck. The most common of all occupational disorders associated with diving are otologic diseases. External otitis has been reported as the most common otolaryngologic problem in underwater divers. Exostosis of the external ear canal may be formed in divers as the result of prolonged diving in cold waters. Other disorders of the ear and paranasal sinuses in underwater divers are caused by barometric pressure change (i.e., barotraumas, and to a lesser extent by decompression sickness. Barotrauma of the middle ear is the most prevalent barotrauma in divers. The inner ear barotraumas, though important, is less common. The present paper is a brief overview of diving-related ear disorders particularly in scuba divers.

EARS: Electronic Access to Reference Service.

Science.gov (United States)

Weise, F O; Borgendale, M

1986-10-01

Electronic Access to Reference Service (EARS) is a front end to the Health Sciences Library's electronic mail system, with links to the online public catalog. EARS, which became operational in September 1984, is accessed by users at remote sites with either a terminal or microcomputer. It is menu-driven, allowing users to request: a computerized literature search, reference information, a photocopy of a journal article, or a book. This paper traces the history of EARS and discusses its use, its impact on library staff and services, and factors that influence the diffusion of new technology.

Segment-based acoustic models for continuous speech recognition

Science.gov (United States)

Ostendorf, Mari; Rohlicek, J. R.

1993-07-01

This research aims to develop new and more accurate stochastic models for speaker-independent continuous speech recognition, by extending previous work in segment-based modeling and by introducing a new hierarchical approach to representing intra-utterance statistical dependencies. These techniques, which are more costly than traditional approaches because of the large search space associated with higher order models, are made feasible through rescoring a set of HMM-generated N-best sentence hypotheses. We expect these different modeling techniques to result in improved recognition performance over that achieved by current systems, which handle only frame-based observations and assume that these observations are independent given an underlying state sequence. In the fourth quarter of the project, we have completed the following: (1) ported our recognition system to the Wall Street Journal task, a standard task in the ARPA community; (2) developed an initial dependency-tree model of intra-utterance observation correlation; and (3) implemented baseline language model estimation software. Our initial results on the Wall Street Journal task are quite good and represent significantly improved performance over most HMM systems reporting on the Nov. 1992 5k vocabulary test set.

Radar Target Recognition Based on Stacked Denoising Sparse Autoencoder

Directory of Open Access Journals (Sweden)

Zhao Feixiang

2017-04-01

Full Text Available Feature extraction is a key step in radar target recognition. The quality of the extracted features determines the performance of target recognition. However, obtaining the deep nature of the data is difficult using the traditional method. The autoencoder can learn features by making use of data and can obtain feature expressions at different levels of data. To eliminate the influence of noise, the method of radar target recognition based on stacked denoising sparse autoencoder is proposed in this paper. This method can extract features directly and efficiently by setting different hidden layers and numbers of iterations. Experimental results show that the proposed method is superior to the K-nearest neighbor method and the traditional stacked autoencoder.

Automatic Recognition Method for Optical Measuring Instruments Based on Machine Vision

Institute of Scientific and Technical Information of China (English)

SONG Le; LIN Yuchi; HAO Liguo

2008-01-01

Based on a comprehensive study of various algorithms, the automatic recognition of traditional ocular optical measuring instruments is realized. Taking a universal tools microscope (UTM) lens view image as an example, a 2-layer automatic recognition model for data reading is established after adopting a series of pre-processing algorithms. This model is an optimal combination of the correlation-based template matching method and a concurrent back propagation (BP) neural network. Multiple complementary feature extraction is used in generating the eigenvectors of the concurrent network. In order to improve fault-tolerance capacity, rotation invariant features based on Zernike moments are extracted from digit characters and a 4-dimensional group of the outline features is also obtained. Moreover, the operating time and reading accuracy can be adjusted dynamically by setting the threshold value. The experimental result indicates that the newly developed algorithm has optimal recognition precision and working speed. The average reading ratio can achieve 97.23%. The recognition method can automatically obtain the results of optical measuring instruments rapidly and stably without modifying their original structure, which meets the application requirements.

The neural correlates of gist-based true and false recognition

Science.gov (United States)

Gutchess, Angela H.; Schacter, Daniel L.

2012-01-01

When information is thematically related to previously studied information, gist-based processes contribute to false recognition. Using functional MRI, we examined the neural correlates of gist-based recognition as a function of increasing numbers of studied exemplars. Sixteen participants incidentally encoded small, medium, and large sets of pictures, and we compared the neural response at recognition using parametric modulation analyses. For hits, regions in middle occipital, middle temporal, and posterior parietal cortex linearly modulated their activity according to the number of related encoded items. For false alarms, visual, parietal, and hippocampal regions were modulated as a function of the encoded set size. The present results are consistent with prior work in that the neural regions supporting veridical memory also contribute to false memory for related information. The results also reveal that these regions respond to the degree of relatedness among similar items, and implicate perceptual and constructive processes in gist-based false memory. PMID:22155331

The visible ear simulator: a public PC application for GPU-accelerated haptic 3D simulation of ear surgery based on the visible ear data

DEFF Research Database (Denmark)

Sørensen, Mads Sølvsten; Mosegaard, Jesper; Trier, Peter

2009-01-01

material.Virtual training often requires the purchase of a program, a customized computer, and expensive peripherals dedicated exclusively to this purpose. MATERIALS AND METHODS: The Visible Ear freeware library of digital images from a fresh-frozen human temporal bone was segmented, and real-time volume...... is published for download (approximately 120 MB) as freeware at http://www.alexandra.dk/ves/index.htm.With increasing personal computer performance, future versions may include enhanced resolution (up to 8,000 voxels/mm3) and realistic interaction with deformable soft tissue components such as skin, tympanic...

DNA isolation from rat tail or ear

NARCIS (Netherlands)

Cuppen, E.

2010-01-01

This protocol describes a rapid procedure for isolating DNA from rat tail or ear punches. The simplest version of the protocol can be scaled for use in 96-well (deep-well) plates. The quality of the DNA is sufficient for any polymerase chain reaction (PCR)-based genotyping approach.

Feature and score fusion based multiple classifier selection for iris recognition.

Science.gov (United States)

Islam, Md Rabiul

2014-01-01

The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al.

Feature and Score Fusion Based Multiple Classifier Selection for Iris Recognition

Directory of Open Access Journals (Sweden)

Md. Rabiul Islam

2014-01-01

Full Text Available The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al.

MRI measurement for inner ear structures

International Nuclear Information System (INIS)

Li Shuling; Liu Huaijun; Chi Chen; Qin Ruiping; Shi Zhaoxia

2003-01-01

Objective: To reconstruct the image of inner ear by using 3D-FASE heavily T 2 WI, and to establish MRI measurement criterion of inner ear structures. Methods: One hundred and six inner ears of 53 healthy volunteers underwent MRI heavily T2-weighted axial scanning by using 3D fast advanced spin echo sequence. All the original images were transferred to an online workstation. Analyze AVW software was used for image post-processing. All the structures of inner ear were reconstructed, rotated from various angles and measured by using maximum intensity projection (MIP). Results: (1) All the structures of inner ear and internal auditory channel (IAC) could be visualized clearly by using 3D-FASE heavily T 2 WI. (2) Using analysis of variance, there was no age, side or race-related difference in inner ear volume, but it was bigger in male than in female [(0.242 ± 0.0236) mm 3 (male) versus (0.226 ± 0.021) mm 3 (female)]. There was no age, side-related differences in three semicircular canal height and vestibule vertical diameter, but, again, they were bigger in male than in female. The height of upper, lateral and posterior semicircular canal were (5.511 ± 0.626) mm (male) versus (5.167 ± 0.357) mm (female); (3.763 ± 0.495) mm (male) versus (3.446 ± 0.405) mm (female); (5.227 ± 0.547) mm (male) versus (4.786 ± 0.500) mm (female). There was no age, sex or side-related differences in three semicircular canal diameter and cochlea. The diameter of upper, lateral and posterior semicircular canal were (1.06 ± 0.119) mm, (1.14 ± 0.181) mm, and (1.22 ± 0.196)mm; the external diameter of cochlea basal turn was (6.520 ± 0.475) mm, the diameter of cochlea basal turn was (1.413 ± 0.144) mm, and cochlea height was (4.100 ± 0.405) mm. Conclusion: (1) For the first time, the MRI measurement criterion of inner ear structures is established. (2) Vestibule and three semicircular canal of inner ear are bigger in male than in female

Pathology of ear hematomas in swine.

Science.gov (United States)

Drolet, Richard; Hélie, Pierre; D'Allaire, Sylvie

2016-05-01

The objectives of our study were to describe the pathology of ear hematomas in swine and to add to the comprehension of the pathogenesis of this condition. The pathogenesis of aural hematomas has been studied mainly in dogs; however, disagreements exist about the precise anatomic location of the hemorrhage. Sixteen pigs with ear hematoma at various stages of development were included in this study. The pigs were submitted for routine autopsy for various and unrelated reasons over a period of several years. Based on gross examination, the 16 cases of aural hematomas were subjectively classified as acute (n = 6), subacute (n = 3), and chronic (n = 7). The age of the animals at the time of autopsy ranged from 2 weeks to adulthood, with all acute cases being hematoma developed predominantly in a subperichondral location on both sides of the cartilaginous plate simultaneously. Within these same cases, there were also some areas in which blood-filled clefts had formed within the cartilage itself. Besides fibroplasia, neoformation of cartilage was found to represent a significant part of the repair process. All chronic cases were characterized on cross-section of the ear by the presence of at least 2 distinct, wavy, focally folded, and roughly parallel plates of cartilage separated from each other by fibrous tissue. © 2016 The Author(s).

Development and validation of a smartphone-based digits-in-noise hearing test in South African English.

Science.gov (United States)

Potgieter, Jenni-Marí; Swanepoel, De Wet; Myburgh, Hermanus Carel; Hopper, Thomas Christopher; Smits, Cas

2015-07-01

The objective of this study was to develop and validate a smartphone-based digits-in-noise hearing test for South African English. Single digits (0-9) were recorded and spoken by a first language English female speaker. Level corrections were applied to create a set of homogeneous digits with steep speech recognition functions. A smartphone application was created to utilize 120 digit-triplets in noise as test material. An adaptive test procedure determined the speech reception threshold (SRT). Experiments were performed to determine headphones effects on the SRT and to establish normative data. Participants consisted of 40 normal-hearing subjects with thresholds ≤15 dB across the frequency spectrum (250-8000 Hz) and 186 subjects with normal-hearing in both ears, or normal-hearing in the better ear. The results show steep speech recognition functions with a slope of 20%/dB for digit-triplets presented in noise using the smartphone application. The results of five headphone types indicate that the smartphone-based hearing test is reliable and can be conducted using standard Android smartphone headphones or clinical headphones. A digits-in-noise hearing test was developed and validated for South Africa. The mean SRT and speech recognition functions correspond to previous developed telephone-based digits-in-noise tests.

Automatic Recognition of Chinese Personal Name Using Conditional Random Fields and Knowledge Base

Directory of Open Access Journals (Sweden)

Chuan Gu

2015-01-01

Full Text Available According to the features of Chinese personal name, we present an approach for Chinese personal name recognition based on conditional random fields (CRF and knowledge base in this paper. The method builds multiple features of CRF model by adopting Chinese character as processing unit, selects useful features based on selection algorithm of knowledge base and incremental feature template, and finally implements the automatic recognition of Chinese personal name from Chinese document. The experimental results on open real corpus demonstrated the effectiveness of our method and obtained high accuracy rate and high recall rate of recognition.

A longitudinal study of methanol in the exhaled breath of 30 healthy volunteers using selected ion flow tube mass spectrometry, SIFT-MS

Czech Academy of Sciences Publication Activity Database

Turner, C.; Španěl, Patrik; Smith, D.

2006-01-01

Roč. 27, č. 7 (2006), s. 637-648 ISSN 0967-3334 Institutional research plan: CEZ:AV0Z40400503 Keywords : SIFT-MS * mass spectrometry * methanol Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.438, year: 2006

Comparing source-based and gist-based false recognition in aging and Alzheimer's disease.

Science.gov (United States)

Pierce, Benton H; Sullivan, Alison L; Schacter, Daniel L; Budson, Andrew E

2005-07-01

This study examined 2 factors contributing to false recognition of semantic associates: errors based on confusion of source and errors based on general similarity information or gist. The authors investigated these errors in patients with Alzheimer's disease (AD), age-matched control participants, and younger adults, focusing on each group's ability to use recollection of source information to suppress false recognition. The authors used a paradigm consisting of both deep and shallow incidental encoding tasks, followed by study of a series of categorized lists in which several typical exemplars were omitted. Results showed that healthy older adults were able to use recollection from the deep processing task to some extent but less than that used by younger adults. In contrast, false recognition in AD patients actually increased following the deep processing task, suggesting that they were unable to use recollection to oppose familiarity arising from incidental presentation. (c) 2005 APA, all rights reserved.

Ear, Hearing and Speech

DEFF Research Database (Denmark)

Poulsen, Torben

2000-01-01

An introduction is given to the the anatomy and the function of the ear, basic psychoacoustic matters (hearing threshold, loudness, masking), the speech signal and speech intelligibility. The lecture note is written for the course: Fundamentals of Acoustics and Noise Control (51001)......An introduction is given to the the anatomy and the function of the ear, basic psychoacoustic matters (hearing threshold, loudness, masking), the speech signal and speech intelligibility. The lecture note is written for the course: Fundamentals of Acoustics and Noise Control (51001)...

Biometric verification based on grip-pattern recognition

NARCIS (Netherlands)

Veldhuis, Raymond N.J.; Bazen, A.M.; Kauffman, J.A.; Hartel, Pieter H.; Delp, Edward J.; Wong, Ping W.

This paper describes the design, implementation and evaluation of a user-verification system for a smart gun, which is based on grip-pattern recognition. An existing pressure sensor consisting of an array of 44 x 44 piezoresistive elements is used to measure the grip pattern. An interface has been

Biometric verification based on grip-pattern recognition

NARCIS (Netherlands)

Veldhuis, Raymond N.J.; Bazen, A.M.; Kauffman, J.A.; Hartel, Pieter H.

This paper describes the design, implementation and evaluation of a user-verification system for a smart gun, which is based on grip-pattern recognition. An existing pressure sensor consisting of an array of 44 £ 44 piezoresistive elements is used to measure the grip pattern. An interface has been

Phonological variation in verbs ending in –ear (chantagear and –iar (variar

Directory of Open Access Journals (Sweden)

Thaïs Cristófaro Alves da Silva

2009-10-01

Full Text Available This paper deals with the variation between mid and high vowels related to verbal forms in Brazilian Portuguese ending in –ear  (chantagear “to blackmail” and –iar (variar “to vary”. In these two sets of verbs one observes standard forms such as chantag[e]ia  and var[i]a and also non-standard forms such as chantag[i]a and  var[i]ia. It will also be considered regular verbs in –ear that did not show variation: estr[Ei]a.  Based on Usage-Based Phonology (BYBEE, 2001 and Exemplar Model (PIERREHUMBERT, 2001 we will show that in verbs ending in -ear and –iar type frequency and special verbs contribute to speakers generalize morphological  marked patterns. This offer instruments to explain why speaker generalize morphophonological patterns for verbs ending in –ear  (chantagear as verbs ending in –iar (variar. We will also explain why a form like estr[Ei]a does not present variation.

A break-even analysis of major ear surgery.

Science.gov (United States)

Wasson, J D; Phillips, J S

2015-10-01

To determine variables which affect cost and profit for major ear surgery and perform a break-even analysis. Retrospective financial analysis. UK teaching hospital. Patients who underwent major ear surgery under general anaesthesia performed by the senior author in main theatre over a 2-year period between dates of 07 September 2010 and 07 September 2012. Income, cost and profit for each major ear patient spell. Variables that affect major ear surgery profitability. Seventy-six patients met inclusion criteria. Wide variation in earnings, with a median net loss of £-1345.50 was observed. Income was relatively uniform across all patient spells; however, theatre time of major ear surgery at a cost of £953.24 per hour varied between patients and was the main determinant of cost and profit for the patient spell. Bivariate linear regression of earnings on theatre time identified 94% of variation in earnings was due to variation in theatre time (r = -0.969; P break-even time for major ear surgery of 110.6 min. Theatre time was dependent on complexity of procedure and number of OPCS4 procedures performed, with a significant increase in theatre time when three or more procedures were performed during major ear surgery (P = 0.015). For major ear surgery to either break-even or return a profit, total theatre time should not exceed 110 min and 36 s. © 2015 John Wiley & Sons Ltd.

Generation of inner ear organoids containing functional hair cells from human pluripotent stem cells.

Science.gov (United States)

Koehler, Karl R; Nie, Jing; Longworth-Mills, Emma; Liu, Xiao-Ping; Lee, Jiyoon; Holt, Jeffrey R; Hashino, Eri

2017-06-01

The derivation of human inner ear tissue from pluripotent stem cells would enable in vitro screening of drug candidates for the treatment of hearing and balance dysfunction and may provide a source of cells for cell-based therapies of the inner ear. Here we report a method for differentiating human pluripotent stem cells to inner ear organoids that harbor functional hair cells. Using a three-dimensional culture system, we modulate TGF, BMP, FGF, and WNT signaling to generate multiple otic-vesicle-like structures from a single stem-cell aggregate. Over 2 months, the vesicles develop into inner ear organoids with sensory epithelia that are innervated by sensory neurons. Additionally, using CRISPR-Cas9, we generate an ATOH1-2A-eGFP cell line to detect hair cell induction and demonstrate that derived hair cells exhibit electrophysiological properties similar to those of native sensory hair cells. Our culture system should facilitate the study of human inner ear development and research on therapies for diseases of the inner ear.

FAST COMMUNICATION: A PDE Based Two Level Model of the Masking Property of the Human Ear

OpenAIRE

Xin, Jack; Qi, Yingyong

2003-01-01

Human ear has the masking property that certain audible sound becomes inaudible in the presence of another sound. Masking is quantified by the raised threshold from the absolute hearing threshold in quiet. It is of scientific and practical importance to compute masking thresholds. Empirical models on masking have applications in low bit rate digital music compression. A first principle based two level model is developed with partial differential equation (PDE) at the periphe...

Leader/Follower Behaviour Using the SIFT Algorithm for Object Recognition

Science.gov (United States)

2006-06-01

opérations de convoiement plus complexes qui utiliseraient une vision artificielle basée sur la détection d’un chef. Les travaux futurs : Étant donné la...Systems: A Virtual Trailer Link Model, In Proceedings of IEEE/RSJ Conference on Intelligent Robots and Systems. [4] Hong, P., Sahli, H., Colon, E., and... Intelligent Robots and Systems. [6] Nguyen, H., Kogut, G., Barua, R., and Burmeister, A. (2004), A Segway RMP-based Robotic Transport System, In In

A Conserved EAR Motif Is Required for Avirulence and Stability of the Ralstonia solanacearum Effector PopP2 In Planta

Directory of Open Access Journals (Sweden)

Cécile Segonzac

2017-08-01

Full Text Available Ralstonia solanacearum is the causal agent of the devastating bacterial wilt disease in many high value Solanaceae crops. R. solanacearum secretes around 70 effectors into host cells in order to promote infection. Plants have, however, evolved specialized immune receptors that recognize corresponding effectors and confer qualitative disease resistance. In the model species Arabidopsis thaliana, the paired immune receptors RRS1 (resistance to Ralstonia solanacearum 1 and RPS4 (resistance to Pseudomonas syringae 4 cooperatively recognize the R. solanacearum effector PopP2 in the nuclei of infected cells. PopP2 is an acetyltransferase that binds to and acetylates the RRS1 WRKY DNA-binding domain resulting in reduced RRS1-DNA association thereby activating plant immunity. Here, we surveyed the naturally occurring variation in PopP2 sequence among the R. solanacearum strains isolated from diseased tomato and pepper fields across the Republic of Korea. Our analysis revealed high conservation of popP2 sequence with only three polymorphic alleles present amongst 17 strains. Only one variation (a premature stop codon caused the loss of RPS4/RRS1-dependent recognition in Arabidopsis. We also found that PopP2 harbors a putative eukaryotic transcriptional repressor motif (ethylene-responsive element binding factor-associated amphiphilic repression or EAR, which is known to be involved in the recruitment of transcriptional co-repressors. Remarkably, mutation of the EAR motif disabled PopP2 avirulence function as measured by the development of hypersensitive response, electrolyte leakage, defense marker gene expression and bacterial growth in Arabidopsis. This lack of recognition was partially but significantly reverted by the C-terminal addition of a synthetic EAR motif. We show that the EAR motif-dependent gain of avirulence correlated with the stability of the PopP2 protein. Furthermore, we demonstrated the requirement of the PopP2 EAR motif for PTI

Hand-Geometry Recognition Based on Contour Parameters

NARCIS (Netherlands)

Veldhuis, Raymond N.J.; Bazen, A.M.; Booij, W.D.T.; Hendrikse, A.J.; Jain, A.K.; Ratha, N.K.

This paper demonstrates the feasibility of a new method of hand-geometry recognition based on parameters derived from the contour of the hand. The contour is completely determined by the black-and-white image of the hand and can be derived from it by means of simple image-processing techniques. It

Influence of weakly bound adduct ions on breath trace gas analysis by selected ion flow tube mass spectrometry (SIFT-MS)

Czech Academy of Sciences Publication Activity Database

Španěl, Patrik; Smith, D.

2009-01-01

Roč. 280, 1-3 (2009), s. 128-135 ISSN 1387-3806 R&D Projects: GA AV ČR IAA400400702 Institutional research plan: CEZ:AV0Z40400503 Keywords : ion-molecule association * adduct ion * SIFT-MS * breath analysis Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.117, year: 2009

Systems and methods for biometric identification using the acoustic properties of the ear canal

International Nuclear Information System (INIS)

Bouchard, A.M.; Osbourn, G.C.

1998-01-01

The present invention teaches systems and methods for verifying or recognizing a person's identity based on measurements of the acoustic response of the individual's ear canal. The system comprises an acoustic emission device, which emits an acoustic source signal s(t), designated by a computer, into the ear canal of an individual, and an acoustic response detection device, which detects the acoustic response signal f(t). A computer digitizes the response (detected) signal f(t) and stores the data. Computer-implemented algorithms analyze the response signal f(t) to produce ear-canal feature data. The ear-canal feature data obtained during enrollment is stored on the computer, or some other recording medium, to compare the enrollment data with ear-canal feature data produced in a subsequent access attempt, to determine if the individual has previously been enrolled. The system can also be adapted for remote access applications. 5 figs

Systems and methods for biometric identification using the acoustic properties of the ear canal

Science.gov (United States)

Bouchard, Ann Marie; Osbourn, Gordon Cecil

1998-01-01

The present invention teaches systems and methods for verifying or recognizing a person's identity based on measurements of the acoustic response of the individual's ear canal. The system comprises an acoustic emission device, which emits an acoustic source signal s(t), designated by a computer, into the ear canal of an individual, and an acoustic response detection device, which detects the acoustic response signal f(t). A computer digitizes the response (detected) signal f(t) and stores the data. Computer-implemented algorithms analyze the response signal f(t) to produce ear-canal feature data. The ear-canal feature data obtained during enrollment is stored on the computer, or some other recording medium, to compare the enrollment data with ear-canal feature data produced in a subsequent access attempt, to determine if the individual has previously been enrolled. The system can also be adapted for remote access applications.

Inner ear malformations in siblings presenting with vestibular ...

African Journals Online (AJOL)

Although the association between inner ear abnormalities and progressive sensorineural hearing loss is well known, vestibular signs or loss of vestibular function in these ... We provide a brief overview of the latest classification of these inner ear defects as well as a review of the literature pertaining to children with inner ear ...

Chinese character recognition based on Gabor feature extraction and CNN

Science.gov (United States)

Xiong, Yudian; Lu, Tongwei; Jiang, Yongyuan

2018-03-01

As an important application in the field of text line recognition and office automation, Chinese character recognition has become an important subject of pattern recognition. However, due to the large number of Chinese characters and the complexity of its structure, there is a great difficulty in the Chinese character recognition. In order to solve this problem, this paper proposes a method of printed Chinese character recognition based on Gabor feature extraction and Convolution Neural Network(CNN). The main steps are preprocessing, feature extraction, training classification. First, the gray-scale Chinese character image is binarized and normalized to reduce the redundancy of the image data. Second, each image is convoluted with Gabor filter with different orientations, and the feature map of the eight orientations of Chinese characters is extracted. Third, the feature map through Gabor filters and the original image are convoluted with learning kernels, and the results of the convolution is the input of pooling layer. Finally, the feature vector is used to classify and recognition. In addition, the generalization capacity of the network is improved by Dropout technology. The experimental results show that this method can effectively extract the characteristics of Chinese characters and recognize Chinese characters.

A convenient method for calculation of ionic diffusion coefficients for accurate selected ion flow tube mass spectrometry, SIFT-MS

Czech Academy of Sciences Publication Activity Database

Dryahina, Kseniya; Španěl, Patrik

2005-01-01

Roč. 244, 2-3 (2005), s. 148-154 ISSN 1387-3806 R&D Projects: GA ČR GA202/03/0827; GA AV ČR KSK4040110 Institutional research plan: CEZ:AV0Z40400503 Keywords : mobility * diffusion * SIFT-MS * ion geometry * interaction potential Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.090, year: 2005

Emotion recognition based on multiple order features using fractional Fourier transform

Science.gov (United States)

Ren, Bo; Liu, Deyin; Qi, Lin

2017-07-01

In order to deal with the insufficiency of recently algorithms based on Two Dimensions Fractional Fourier Transform (2D-FrFT), this paper proposes a multiple order features based method for emotion recognition. Most existing methods utilize the feature of single order or a couple of orders of 2D-FrFT. However, different orders of 2D-FrFT have different contributions on the feature extraction of emotion recognition. Combination of these features can enhance the performance of an emotion recognition system. The proposed approach obtains numerous features that extracted in different orders of 2D-FrFT in the directions of x-axis and y-axis, and uses the statistical magnitudes as the final feature vectors for recognition. The Support Vector Machine (SVM) is utilized for the classification and RML Emotion database and Cohn-Kanade (CK) database are used for the experiment. The experimental results demonstrate the effectiveness of the proposed method.

Posture recognition based on fuzzy logic for home monitoring of the elderly.

Science.gov (United States)

Brulin, Damien; Benezeth, Yannick; Courtial, Estelle

2012-09-01

We propose in this paper a computer vision-based posture recognition method for home monitoring of the elderly. The proposed system performs human detection prior to the posture analysis; posture recognition is performed only on a human silhouette. The human detection approach has been designed to be robust to different environmental stimuli. Thus, posture is analyzed with simple and efficient features that are not designed to manage constraints related to the environment but only designed to describe human silhouettes. The posture recognition method, based on fuzzy logic, identifies four static postures and is robust to variation in the distance between the camera and the person, and to the person's morphology. With an accuracy of 74.29% of satisfactory posture recognition, this approach can detect emergency situations such as a fall within a health smart home.

Palm vein recognition based on directional empirical mode decomposition

Science.gov (United States)

Lee, Jen-Chun; Chang, Chien-Ping; Chen, Wei-Kuei

2014-04-01

Directional empirical mode decomposition (DEMD) has recently been proposed to make empirical mode decomposition suitable for the processing of texture analysis. Using DEMD, samples are decomposed into a series of images, referred to as two-dimensional intrinsic mode functions (2-D IMFs), from finer to large scale. A DEMD-based 2 linear discriminant analysis (LDA) for palm vein recognition is proposed. The proposed method progresses through three steps: (i) a set of 2-D IMF features of various scale and orientation are extracted using DEMD, (ii) the 2LDA method is then applied to reduce the dimensionality of the feature space in both the row and column directions, and (iii) the nearest neighbor classifier is used for classification. We also propose two strategies for using the set of 2-D IMF features: ensemble DEMD vein representation (EDVR) and multichannel DEMD vein representation (MDVR). In experiments using palm vein databases, the proposed MDVR-based 2LDA method achieved recognition accuracy of 99.73%, thereby demonstrating its feasibility for palm vein recognition.

Improving a Deep Learning based RGB-D Object Recognition Model by Ensemble Learning

DEFF Research Database (Denmark)

Aakerberg, Andreas; Nasrollahi, Kamal; Heder, Thomas

2018-01-01

Augmenting RGB images with depth information is a well-known method to significantly improve the recognition accuracy of object recognition models. Another method to im- prove the performance of visual recognition models is ensemble learning. However, this method has not been widely explored...... in combination with deep convolutional neural network based RGB-D object recognition models. Hence, in this paper, we form different ensembles of complementary deep convolutional neural network models, and show that this can be used to increase the recognition performance beyond existing limits. Experiments...

Ear-body lift and a novel thrust generating mechanism revealed by the complex wake of brown long-eared bats (Plecotus auritus)

Science.gov (United States)

Johansson, L. Christoffer; Håkansson, Jonas; Jakobsen, Lasse; Hedenström, Anders

2016-04-01

Large ears enhance perception of echolocation and prey generated sounds in bats. However, external ears likely impair aerodynamic performance of bats compared to birds. But large ears may generate lift on their own, mitigating the negative effects. We studied flying brown long-eared bats, using high resolution, time resolved particle image velocimetry, to determine the aerodynamics of flying with large ears. We show that the ears and body generate lift at medium to cruising speeds (3-5 m/s), but at the cost of an interaction with the wing root vortices, likely reducing inner wing performance. We also propose that the bats use a novel wing pitch mechanism at the end of the upstroke generating thrust at low speeds, which should provide effective pitch and yaw control. In addition, the wing tip vortices show a distinct spiraling pattern. The tip vortex of the previous wingbeat remains into the next wingbeat and rotates together with a newly formed tip vortex. Several smaller vortices, related to changes in circulation around the wing also spiral the tip vortex. Our results thus show a new level of complexity in bat wakes and suggest large eared bats are less aerodynamically limited than previous wake studies have suggested.

Wavelet-based ground vehicle recognition using acoustic signals

Science.gov (United States)

Choe, Howard C.; Karlsen, Robert E.; Gerhart, Grant R.; Meitzler, Thomas J.

1996-03-01

We present, in this paper, a wavelet-based acoustic signal analysis to remotely recognize military vehicles using their sound intercepted by acoustic sensors. Since expedited signal recognition is imperative in many military and industrial situations, we developed an algorithm that provides an automated, fast signal recognition once implemented in a real-time hardware system. This algorithm consists of wavelet preprocessing, feature extraction and compact signal representation, and a simple but effective statistical pattern matching. The current status of the algorithm does not require any training. The training is replaced by human selection of reference signals (e.g., squeak or engine exhaust sound) distinctive to each individual vehicle based on human perception. This allows a fast archiving of any new vehicle type in the database once the signal is collected. The wavelet preprocessing provides time-frequency multiresolution analysis using discrete wavelet transform (DWT). Within each resolution level, feature vectors are generated from statistical parameters and energy content of the wavelet coefficients. After applying our algorithm on the intercepted acoustic signals, the resultant feature vectors are compared with the reference vehicle feature vectors in the database using statistical pattern matching to determine the type of vehicle from where the signal originated. Certainly, statistical pattern matching can be replaced by an artificial neural network (ANN); however, the ANN would require training data sets and time to train the net. Unfortunately, this is not always possible for many real world situations, especially collecting data sets from unfriendly ground vehicles to train the ANN. Our methodology using wavelet preprocessing and statistical pattern matching provides robust acoustic signal recognition. We also present an example of vehicle recognition using acoustic signals collected from two different military ground vehicles. In this paper, we will

earGram Actors: An Interactive Audiovisual System Based on Social Behavior

Directory of Open Access Journals (Sweden)

Peter Beyls

2015-11-01

Full Text Available In multi-agent systems, local interactions among system components following relatively simple rules often result in complex overall systemic behavior. Complex behavioral and morphological patterns have been used to generate and organize audiovisual systems with artistic purposes. In this work, we propose to use the Actor model of social interactions to drive a concatenative synthesis engine called earGram in real time. The Actor model was originally developed to explore the emergence of complex visual patterns. On the other hand, earGram was originally developed to facilitate the creative exploration of concatenative sound synthesis. The integrated audiovisual system allows a human performer to interact with the system dynamics while receiving visual and auditory feedback. The interaction happens indirectly by disturbing the rules governing the social relationships amongst the actors, which results in a wide range of dynamic spatiotemporal patterns. A performer thus improvises within the behavioural scope of the system while evaluating the apparent connections between parameter values and actual complexity of the system output.

Hypergraph-Based Recognition Memory Model for Lifelong Experience

Science.gov (United States)

2014-01-01

Cognitive agents are expected to interact with and adapt to a nonstationary dynamic environment. As an initial process of decision making in a real-world agent interaction, familiarity judgment leads the following processes for intelligence. Familiarity judgment includes knowing previously encoded data as well as completing original patterns from partial information, which are fundamental functions of recognition memory. Although previous computational memory models have attempted to reflect human behavioral properties on the recognition memory, they have been focused on static conditions without considering temporal changes in terms of lifelong learning. To provide temporal adaptability to an agent, in this paper, we suggest a computational model for recognition memory that enables lifelong learning. The proposed model is based on a hypergraph structure, and thus it allows a high-order relationship between contextual nodes and enables incremental learning. Through a simulated experiment, we investigate the optimal conditions of the memory model and validate the consistency of memory performance for lifelong learning. PMID:25371665

Finger vein recognition based on convolutional neural network

Directory of Open Access Journals (Sweden)

Meng Gesi

2017-01-01

Full Text Available Biometric Authentication Technology has been widely used in this information age. As one of the most important technology of authentication, finger vein recognition attracts our attention because of its high security, reliable accuracy and excellent performance. However, the current finger vein recognition system is difficult to be applied widely because its complicated image pre-processing and not representative feature vectors. To solve this problem, a finger vein recognition method based on the convolution neural network (CNN is proposed in the paper. The image samples are directly input into the CNN model to extract its feature vector so that we can make authentication by comparing the Euclidean distance between these vectors. Finally, the Deep Learning Framework Caffe is adopted to verify this method. The result shows that there are great improvements in both speed and accuracy rate compared to the previous research. And the model has nice robustness in illumination and rotation.

Naturopathic treatment for ear pain in children.

Science.gov (United States)

Sarrell, E Michael; Cohen, Herman Avner; Kahan, Ernesto

2003-05-01

included in the study and recorded all of the data. The presence or absence of ear pain was assessed over 3 days with a visual analog scale. Ear pain was assessed by a specially devised observational instrument based on previous reports. One side of the instrument consisted of a linear numbered scale, from 1 (no pain) to 10 (worst possible pain), and a corresponding color scale, ranging from blue to dark red. The reverse side contained a scale of 5 facial expressions, ranging from broad smile (no pain) to a sad and crying face (worst possible pain), and a corresponding color scale, ranging from blue to dark red. There were no significant between-group differences in patient age or gender, degree of fever, main symptoms, associated symptoms, and severity or laterality of acute otitis media. Each group had a statistically significant improvement in ear pain over the course of the 3 days. Patients who were given ear drops alone had a better response than patients who were given ear drops together with amoxicillin. Results were better in the NHED group than in the controls. Nevertheless, the findings indicated that the pain was mostly (80%) self-limited and could be explained simply by the time elapsed. The American Academy of Otolaryngology-Head and Neck Surgery guidelines recommend topical medications as the first line of treatment for ear pain in the absence of systemic infection or serious underlying disease. Because no evidence was found that systemic antibiotics alone improved treatment outcome, if antibiotics do not change the natural course of otitis media, then the main goal of treatment, as in the present study, should be to alleviate the ear pain. The alternative, naturopathic herbal extract medications, may offer many new possibilities in the management of ear pain associated with AOM. Primary care physicians should be aware that at least 10% of their patients may have tried 1 or more forms of alternative/complementary medicine before presenting for consultation

Pattern Recognition-Based Analysis of COPD in CT

DEFF Research Database (Denmark)

Sørensen, Lauge Emil Borch Laurs

recognition part is used to turn the texture measures, measured in a CT image of the lungs, into a quantitative measure of disease. This is done by applying a classifier that is trained on a training set of data examples with known lung tissue patterns. Different classification systems are considered, and we...... will in particular use the pattern recognition concepts of supervised learning, multiple instance learning, and dissimilarity representation-based classification. The proposed texture-based measures are applied to CT data from two different sources, one comprising low dose CT slices from subjects with manually...... annotated regions of emphysema and healthy tissue, and one comprising volumetric low dose CT images from subjects that are either healthy or suffer from COPD. Several experiments demonstrate that it is clearly beneficial to take the lung tissue texture into account when classifying or quantifying emphysema...

ElectroAcoustic Resource Site (EARS)

OpenAIRE

Atkinson, Simon; Landy, Leigh

2002-01-01

Central to the MTIRC’s electroacoustic music studies focus, EARS is supported by the AHRC’s resource enhancement scheme (ca. £170k) and Unesco (£3k). Beyond its initial goal to create the glossary (~500 entries) and related index (providing a coherent hyperlink structure for the bibliography – ~3000 entries) there are further methodological research imperatives – to offer a web-based resource that: a) Realises an accessible research resource (glossary, keyword index and bibliography) to co...

Imaging of the postoperative middle ear

Energy Technology Data Exchange (ETDEWEB)

Williams, Marc T. [Department of Medical Imaging, Fondation Ophtalmologique Adolphe de Rothschild, 25 rue Manin, 75940, Paris (France); Ayache, Denis [Department of Otorhinolaryngology, Fondation Ophtalmologique Adolphe de Rothschild, Paris (France)

2004-03-01

The aim of this article is twofold: (a) to present the principles and the indications of surgical treatment of middle ear pathologies; and (b) to review the imaging findings after middle ear surgery, including the normal postoperative aspects and imaging findings in patients presenting with unsatisfactory surgical results or with suspicion of postoperative complications. This review is intentionally restricted to the most common diseases involving the middle ear: chronic otitis media and otosclerosis. In these specific fields of interest, CT and MR imaging play a very important role in the postoperative follow-up and in the work-up of surgical failures and complications. (orig.)

A SIFT Study of the Reactions of H3O+, NO+ and O2+ with Hydrogen Peroxide and Peroxyacetic Acid

Czech Academy of Sciences Publication Activity Database

Španěl, Patrik; Diskin, A. M.; Wang, T.; Smith, D.

2003-01-01

Roč. 228, - (2003), s. 269-283 ISSN 1387-3806 R&D Projects: GA ČR GA202/03/0827; GA ČR GA203/02/0737 Institutional research plan: CEZ:AV0Z4040901 Keywords : SIFT * hydrogen peroxide * peroxyacetic acid Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.361, year: 2003

Optical-electronic shape recognition system based on synergetic associative memory

Science.gov (United States)

Gao, Jun; Bao, Jie; Chen, Dingguo; Yang, Youqing; Yang, Xuedong

2001-04-01

This paper presents a novel optical-electronic shape recognition system based on synergetic associative memory. Our shape recognition system is composed of two parts: the first one is feature extraction system; the second is synergetic pattern recognition system. Hough transform is proposed for feature extraction of unrecognized object, with the effects of reducing dimensions and filtering for object distortion and noise, synergetic neural network is proposed for realizing associative memory in order to eliminate spurious states. Then we adopt an approach of optical- electronic realization to our system that can satisfy the demands of real time, high speed and parallelism. In order to realize fast algorithm, we replace the dynamic evolution circuit with adjudge circuit according to the relationship between attention parameters and order parameters, then implement the recognition of some simple images and its validity is proved.

Bionic Design of Wind Turbine Blade Based on Long-Eared Owl's Airfoil.

Science.gov (United States)

Tian, Weijun; Yang, Zhen; Zhang, Qi; Wang, Jiyue; Li, Ming; Ma, Yi; Cong, Qian

2017-01-01

The main purpose of this paper is to demonstrate a bionic design for the airfoil of wind turbines inspired by the morphology of Long-eared Owl's wings. Glauert Model was adopted to design the standard blade and the bionic blade, respectively. Numerical analysis method was utilized to study the aerodynamic characteristics of the airfoils as well as the blades. Results show that the bionic airfoil inspired by the airfoil at the 50% aspect ratio of the Long-eared Owl's wing gives rise to a superior lift coefficient and stalling performance and thus can be beneficial to improving the performance of the wind turbine blade. Also, the efficiency of the bionic blade in wind turbine blades tests increases by 12% or above (up to 44%) compared to that of the standard blade. The reason lies in the bigger pressure difference between the upper and lower surface which can provide stronger lift.

Flexible Piezoelectric Sensor-Based Gait Recognition

Directory of Open Access Journals (Sweden)

Youngsu Cha

2018-02-01

Full Text Available Most motion recognition research has required tight-fitting suits for precise sensing. However, tight-suit systems have difficulty adapting to real applications, because people normally wear loose clothes. In this paper, we propose a gait recognition system with flexible piezoelectric sensors in loose clothing. The gait recognition system does not directly sense lower-body angles. It does, however, detect the transition between standing and walking. Specifically, we use the signals from the flexible sensors attached to the knee and hip parts on loose pants. We detect the periodic motion component using the discrete time Fourier series from the signal during walking. We adapt the gait detection method to a real-time patient motion and posture monitoring system. In the monitoring system, the gait recognition operates well. Finally, we test the gait recognition system with 10 subjects, for which the proposed system successfully detects walking with a success rate over 93 %.

Optical character recognition of camera-captured images based on phase features

Science.gov (United States)

Diaz-Escobar, Julia; Kober, Vitaly

2015-09-01

Nowadays most of digital information is obtained using mobile devices specially smartphones. In particular, it brings the opportunity for optical character recognition in camera-captured images. For this reason many recognition applications have been recently developed such as recognition of license plates, business cards, receipts and street signal; document classification, augmented reality, language translator and so on. Camera-captured images are usually affected by geometric distortions, nonuniform illumination, shadow, noise, which make difficult the recognition task with existing systems. It is well known that the Fourier phase contains a lot of important information regardless of the Fourier magnitude. So, in this work we propose a phase-based recognition system exploiting phase-congruency features for illumination/scale invariance. The performance of the proposed system is tested in terms of miss classifications and false alarms with the help of computer simulation.

Proteomics and the Inner Ear

Directory of Open Access Journals (Sweden)

Isolde Thalmann

2001-01-01

Full Text Available The inner ear, one of the most complex organs, contains within its bony shell three sensory systems, the evolutionary oldest gravity receptor system, the three semicircular canals for the detection of angular acceleration, and the auditory system - unrivaled in sensitivity and frequency discrimination. All three systems are susceptible to a host of afflictions affecting the quality of life for all of us. In the first part of this review we present an introduction to the milestones of inner ear research to pave the way for understanding the complexities of a proteomics approach to the ear. Minute sensory structures, surrounded by large fluid spaces and a hard bony shell, pose extreme challenges to the ear researcher. In spite of these obstacles, a powerful preparatory technique was developed, whereby precisely defined microscopic tissue elements can be isolated and analyzed, while maintaining the biochemical state representative of the in vivo conditions. The second part consists of a discussion of proteomics as a tool in the elucidation of basic and pathologic mechanisms, diagnosis of disease, as well as treatment. Examples are the organ of Corti proteins OCP1 and OCP2, oncomodulin, a highly specific calcium-binding protein, and several disease entities, Meniere's disease, benign paroxysmal positional vertigo, and perilymphatic fistula.

Aberrant internal carotid artery in the middle ear

Energy Technology Data Exchange (ETDEWEB)

Roh, Keun Tak; Kang, Hyun Koo [Dept. of Radiology, Seoul Veterans Hospital, Seoul (Korea, Republic of)

2014-10-15

The knowledge about the aberrant internal carotid artery (ICA) in the middle ear is essential for clinicians, because a misdiagnosis of the aberrant ICA could have serious consequences such as excessive aural bleeding during a middle ear surgery. A 38-year-old woman presented with tinnitus and hearing difficulties of the left ear that had started 5 years ago. During otoscopy, an anteroinferior bluish mass was seen in the tympanic space. Computed tomography and magnetic resonance imaging demonstrated a left-side aberrant ICA with bony dehiscence of the carotid canal in the middle ear and a reduced diameter of the tympanic ICA. Herein we report a case of an aberrant ICA in the middle ear. We also review the literature regarding this important vascular anomaly of the temporal bone which may lead to disastrous surgical complications.

Aberrant internal carotid artery in the middle ear

International Nuclear Information System (INIS)

Roh, Keun Tak; Kang, Hyun Koo

2014-01-01

The knowledge about the aberrant internal carotid artery (ICA) in the middle ear is essential for clinicians, because a misdiagnosis of the aberrant ICA could have serious consequences such as excessive aural bleeding during a middle ear surgery. A 38-year-old woman presented with tinnitus and hearing difficulties of the left ear that had started 5 years ago. During otoscopy, an anteroinferior bluish mass was seen in the tympanic space. Computed tomography and magnetic resonance imaging demonstrated a left-side aberrant ICA with bony dehiscence of the carotid canal in the middle ear and a reduced diameter of the tympanic ICA. Herein we report a case of an aberrant ICA in the middle ear. We also review the literature regarding this important vascular anomaly of the temporal bone which may lead to disastrous surgical complications.

SIFT – A language technology toolkit to assess the print media coverage of new forms of governance

OpenAIRE

Wüest, Bruno; Amsler, Michael; Schneider, Gerold

2017-01-01

For social scientists, it is increasingly important to explore large text collections without time-consuming human intervention. We are presenting a language technology tool kit that allows researchers of the NCCR Democracy Module 1 to extract information on various forms of governance from a comprehensive multilingual corpus. The tool kit called SIFT allows searching for governance entities and measuring their salience, tonality, issue context and media frames. In substantial terms, our tool...

An MPCA/LDA Based Dimensionality Reduction Algorithm for Face Recognition

Directory of Open Access Journals (Sweden)

Jun Huang

2014-01-01

Full Text Available We proposed a face recognition algorithm based on both the multilinear principal component analysis (MPCA and linear discriminant analysis (LDA. Compared with current traditional existing face recognition methods, our approach treats face images as multidimensional tensor in order to find the optimal tensor subspace for accomplishing dimension reduction. The LDA is used to project samples to a new discriminant feature space, while the K nearest neighbor (KNN is adopted for sample set classification. The results of our study and the developed algorithm are validated with face databases ORL, FERET, and YALE and compared with PCA, MPCA, and PCA + LDA methods, which demonstrates an improvement in face recognition accuracy.

FPGA-Based Implementation of Lithuanian Isolated Word Recognition Algorithm

Directory of Open Access Journals (Sweden)

Tomyslav Sledevič

2013-05-01

Full Text Available The paper describes the FPGA-based implementation of Lithuanian isolated word recognition algorithm. FPGA is selected for parallel process implementation using VHDL to ensure fast signal processing at low rate clock signal. Cepstrum analysis was applied to features extraction in voice. The dynamic time warping algorithm was used to compare the vectors of cepstrum coefficients. A library of 100 words features was created and stored in the internal FPGA BRAM memory. Experimental testing with speaker dependent records demonstrated the recognition rate of 94%. The recognition rate of 58% was achieved for speaker-independent records. Calculation of cepstrum coefficients lasted for 8.52 ms at 50 MHz clock, while 100 DTWs took 66.56 ms at 25 MHz clock.Article in Lithuanian

Optical character recognition based on nonredundant correlation measurements.

Science.gov (United States)

Braunecker, B; Hauck, R; Lohmann, A W

1979-08-15

The essence of character recognition is a comparison between the unknown character and a set of reference patterns. Usually, these reference patterns are all possible characters themselves, the whole alphabet in the case of letter characters. Obviously, N analog measurements are highly redundant, since only K = log(2)N binary decisions are enough to identify one out of N characters. Therefore, we devised K reference patterns accordingly. These patterns, called principal components, are found by digital image processing, but used in an optical analog computer. We will explain the concept of principal components, and we will describe experiments with several optical character recognition systems, based on this concept.

External ear: An analysis of its uniqueness

Directory of Open Access Journals (Sweden)

Ruma Purkait

2016-06-01

Hence, the individuality of every ear has been confirmed which may find use in personal identification studies. The study is a step towards providing scientific support for admitting ear evidence in the Court of Law.

Investigate earing of TWIP steel sheet during deep-drawing process by using crystal plasticity constitutive model

Directory of Open Access Journals (Sweden)

Yang J.

2015-01-01

Full Text Available By combining the nonlinear finite element analysis techniques and crystal plasticity theory, the macroscopic mechanical behaviour of crystalline material, the texture evolution and earing-type characteristics are simulated accurately. In this work, a crystal plasticity model exhibiting deformation twinning is introduced based on crystal plasticity theory and saturation-type hardening laws for FCC metal Fe-22Mn-0.6C TWIP steel. Based on the CPFE model and parameters which have been determined for TWIP steel, a simplified finite element model for deep drawing is promoted by using crystal plasticity constitutive model. The earing characteristics in typical deep-drawing process are simulated well. Further, the drawing forces are calculated and compared to the experimental results from reference. Meanwhile, the impacts of drawing coefficient and initial texture on the earing characteristics are investigated for controlling the earing.

Rapid detection of lipid oxidation in beef muscle packed under modified atmosphere by measuring volatile organic compounds using SIFT-MS

Czech Academy of Sciences Publication Activity Database

Olivares, A.; Dryahina, Kseniya; Španěl, Patrik; Flores, M.

2012-01-01

Roč. 135, č. 3 (2012), s. 1801-1808 ISSN 0308-8146 R&D Projects: GA ČR GP203/09/P172; GA ČR GA203/09/0256 Institutional research plan: CEZ:AV0Z40400503 Keywords : SIFT-MS * beef * oxidation Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 3.334, year: 2012

Comparison of middle latency responses in presbycusis patients with two different speech recognition scores.

Science.gov (United States)

Kirkim, Gunay; Madanoglu, Nevma; Akdas, Ferda; Serbetcioglu, M Bulent

2007-12-01

The purpose of this study is to evaluate whether the middle latency responses (MLR) can be used for an objective differentiation of patients with presbycusis having relatively good (Group I) and relatively poor speech recognition scores (Group II). All the participants of these groups had high frequency down-sloping hearing loss with an average of 26-60 dB HL. Data were collected from two described study groups and a control group, using pure tone audiometry, monosyllabic phonetically balanced word and synthetic sentence identification, as well as MLR. The study groups were compared with the control group. When patients in Group I were compared with the control group, only ipsilateral Na latency of middle latency evoked response was statistically significant in the right ear whereas ipsilateral Na latency in the right ear, ipsilateral and contralateral Na latency in the left ear of the patients in Group II were statistically significant. Thus, as an objective complementary tool for the evaluation of the speech perception ability of the patients with presbycusis, Na latency of MLR may be used in combination with the speech discrimination tests.

[Diagnostic value of high-resolution computed tomography imaging in congenital inner ear malformations].

Science.gov (United States)

Sun, Xiaowei; Ding, Yuanping; Zhang, Jianji; Chen, Ying; Xu, Anting; Dou, Fenfen; Zhang, Zihe

2007-02-01

To observe the inner ear structure with volume rendering (VR) reconstruction and to evaluate the role of high-resolution computed tomography (HRCT) in congenital inner ear malformations. HRCT scanning was performed in 10 patients (20 ears) without ear disease (control group) and 7 patients (11 ears) with inner ear malformations (IEM group) and the original data was processed with VR reconstruction. The inner ear osseous labyrinth structure in the images generated by these techniques was observed respectively in the normal ears and malformation ears. The inner ear osseous labyrinth structure and the relationship was displayed clearly in VR imaging in the control group,meanwhile, characters and degree of malformed structure were also displayed clearly in the IEA group. Of seven patients (11 ears) with congenital inner ear malformations, the axial, MPR and VR images can display the site and degree in 9 ears. VR images were superior to the axial images in displaying the malformations in 2 ears with the small lateral semicircular canal malformations. The malformations included Mondini deformity (7 ears), vestibular and semicircular canal malformations (3 ears), vestibular aqueduct dilate (7 ears, of which 6 ears accompanied by other malformations) , the internal auditory canal malformation (2 ears, all accompanied by other malformations). HRCT can display the normal structure of bone inner ear through high quality VR reconstructions. VR images can also display the site and degree of the malformations three-dimensionally and intuitively. HRCT is valuable in diagnosing the inner ear malformation.

Coupled ears in lizards and crocodilians

DEFF Research Database (Denmark)

Carr, Catherine E; Christensen-Dalsgaard, Jakob; Bierman, Hilary

2016-01-01

Lizard ears are coupled across the pharynx, and are very directional. In consequence all auditory responses should be directional, without a requirement for computation of sound source location. Crocodilian ears are connected through sinuses, and thus less tightly coupled. Coupling may improve th...... range is reviewed in the light of current theories of sound localization....

A survey on vision-based human action recognition

NARCIS (Netherlands)

Poppe, Ronald Walter

Vision-based human action recognition is the process of labeling image sequences with action labels. Robust solutions to this problem have applications in domains such as visual surveillance, video retrieval and human–computer interaction. The task is challenging due to variations in motion

Clinical review of inner ear malformation

International Nuclear Information System (INIS)

Kokai, Hiromi; Oohashi, Masami; Ishikawa, Kazuo; Harada, Kouji; Hiratsuka, Hitoshi; Ogasawara, Makoto; Miyashita, Souji; Terayama, Yoshihiko

2003-01-01

We had 126 patients with inner ear malformation diagnosed with temporal bone computed tomography (CT) scans at Azabu Triology Hospital between 1996 and 2002. We classified cases of inner ear malformation according to Jackler et al. The incidence of inner ear malformation in our series was as follows; labyrinthine anomalies 61% (isolated lateral semicircular canal dysplasia 56%, compound semicircular canal dysplasia 4%, semicircular canal aplasia 1%), cochlear anomalies 24%, enlargement of the vestibular aqueduct 12%, narrow internal auditory canal 2%, complete labyrinthine aplasia 1%, enlargement of the cochlear aqueduct 0%. The most frequent anomaly was isolated lateral semicircular canal dysplasia. We did not detect any significant clinical features in this anomaly. There were 2 patients with cochlear anomalies who had past histories of meningitis. Some patients with enlargement of the vestibular aqueduct had frequent attacks of fluctuating hearing. Clinically it is important to detect patients with inner ear malformation such as cochlear anomalies and enlargement of the vestibular aqueduct usually accompanied by congenital sensorineural hearing loss. For patients with congenital sensorineural hearing loss, we recommend temporal bone CT scan. (author)

Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

Science.gov (United States)

Qin, Jiangyi; Huang, Zhiping; Liu, Chunwu; Su, Shaojing; Zhou, Jing

2015-01-01

A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK) signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.

RGB-D-T based Face Recognition

DEFF Research Database (Denmark)

Nikisins, Olegs; Nasrollahi, Kamal; Greitans, Modris

2014-01-01

Facial images are of critical importance in many real-world applications from gaming to surveillance. The current literature on facial image analysis, from face detection to face and facial expression recognition, are mainly performed in either RGB, Depth (D), or both of these modalities. But......, such analyzes have rarely included Thermal (T) modality. This paper paves the way for performing such facial analyzes using synchronized RGB-D-T facial images by introducing a database of 51 persons including facial images of different rotations, illuminations, and expressions. Furthermore, a face recognition...... algorithm has been developed to use these images. The experimental results show that face recognition using such three modalities provides better results compared to face recognition in any of such modalities in most of the cases....

A step towards development of aid for visually challenged

Indian Academy of Sciences (India)

The work done towards developing a visual aid to help visually challenged people is described in this paper. An ultrasonic device is used for measuring the distance to a nearby object and SIFT algorithm based approach is used for object recognition from the captured image. Features of the recognized object as well as the ...

Implicit recognition based on lateralized perceptual fluency.

Science.gov (United States)

Vargas, Iliana M; Voss, Joel L; Paller, Ken A

2012-02-06

In some circumstances, accurate recognition of repeated images in an explicit memory test is driven by implicit memory. We propose that this "implicit recognition" results from perceptual fluency that influences responding without awareness of memory retrieval. Here we examined whether recognition would vary if images appeared in the same or different visual hemifield during learning and testing. Kaleidoscope images were briefly presented left or right of fixation during divided-attention encoding. Presentation in the same visual hemifield at test produced higher recognition accuracy than presentation in the opposite visual hemifield, but only for guess responses. These correct guesses likely reflect a contribution from implicit recognition, given that when the stimulated visual hemifield was the same at study and test, recognition accuracy was higher for guess responses than for responses with any level of confidence. The dramatic difference in guessing accuracy as a function of lateralized perceptual overlap between study and test suggests that implicit recognition arises from memory storage in visual cortical networks that mediate repetition-induced fluency increments.

Alterations in the Contra lateral Ear in Chronic Otitis Media

Directory of Open Access Journals (Sweden)

Mohammad Ali Damghani

2013-03-01

Full Text Available Introduction: Chronic otitis media (COM, a persistent and durable inflammation and infection of the middle ear, is a common disorder. Alterations in the contralateral ear in sufferers have been observed in recent years. Because only a few studies have been reported in this area, we performed this study in order to assess alterations in the contralateral ear of patients with COM.   Materials and Methods: Cross-sectional and descriptive methods were used in 100 patients with COM who were selected for surgical treatment and admitted to hospital. An information form was completed for all patients including demographic data, medical history of otoscopy and paraclinical examinations such as pure tone audiometry (PTA, tympanometry, Schuller radiography, and high resolution computed tomography (HRCT. All data were processed using SPSS (version 18 software and descriptive statistical tests.   Results: According to otoscopy, PTA, tympanometry and graphical analysis, 60% of patients experienced disorders of the contralateral ear. Otoscopy analysis showed 54% of patients had a disorder of the contralateral ear, with the most common disorder being perforation of the ear drum. PTA showed a 48% incidence of contralateral ear problems (85% conductive hearing impairment; 12.5% sensorineural hearing impairment; 1.2% mixed. A total of 73.2% of patients with conductive hearing loss had a problem across all frequencies, while half of the patients with sensorineural hearing impairment had problems at frequencies greater than 1000 Hz. According to tympanometry, 38% of patients had problem in the contralateral ear. HRCT and Schuller graphical analyses indicated 31.5% and 36% occurrence of contralateral ear disorders, respectively.   Conclusion:  More than 50% of patients with COM in one ear have a chance of also presenting with the disease in the other ear. Outcomes of this study and previous studies have shown that COM should not be perceived as a disease limited

Enhancing Speech Recognition Using Improved Particle Swarm Optimization Based Hidden Markov Model

Directory of Open Access Journals (Sweden)

Lokesh Selvaraj

2014-01-01

Full Text Available Enhancing speech recognition is the primary intention of this work. In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO is suggested. The suggested methodology contains four stages, namely, (i denoising, (ii feature mining (iii, vector quantization, and (iv IPSO based hidden Markov model (HMM technique (IP-HMM. At first, the speech signals are denoised using median filter. Next, characteristics such as peak, pitch spectrum, Mel frequency Cepstral coefficients (MFCC, mean, standard deviation, and minimum and maximum of the signal are extorted from the denoised signal. Following that, to accomplish the training process, the extracted characteristics are given to genetic algorithm based codebook generation in vector quantization. The initial populations are created by selecting random code vectors from the training set for the codebooks for the genetic algorithm process and IP-HMM helps in doing the recognition. At this point the creativeness will be done in terms of one of the genetic operation crossovers. The proposed speech recognition technique offers 97.14% accuracy.

Potential of popcorn germplasm as a source of resistance to ear rot

Directory of Open Access Journals (Sweden)

Railan do Nascimento Ferreira Kurosawa

Full Text Available ABSTRACT Because of its multi-purpose nature, popcorn has sparked the interest of the World Trade Organization as regards fungal contamination by mycotoxins. However, no investigations have been conducted on popcorn for resistance of genotypes to ear rot. The aim of this study was to evaluate the potential of popcorn genotypes as to resistance to ear rot and rotten kernels, as an initial step for the implementation of a breeding program with the popcorn crop in Northern Rio de Janeiro State, Brazil. Thirty-seven accessions from different ecogeographic regions of Latin America were evaluated in 2 cultivation periods, in a randomized block design with 4 replications. We evaluated the incidence of rotten ears, incidence of rotten ears caused by Fusarium spp., severity of ears with Fusarium spp. rot, and incidence of rotten kernels. The results were subjected to analysis of variance, and means were compared by the Scott-Knott clustering test (p < 0.05. A significant effect was observed for all evaluated variables, characterizing them as efficient in the discrimination of genotypic variability for reaction to fungal injuries in popcorn. The gene pool of the tropical and temperate Germplasm Collection evaluated here has the potential to generate superior segregants and provide hybrid combinations with alleles of resistance to diseases affecting ears and stored kernels. Based on the different variables and times, the experiment was conducted, and genotypes L65, L80, and IAC 125 showed the highest levels of resistance.

Contextual System of Symbol Structural Recognition based on an Object-Process Methodology

OpenAIRE

Delalandre, Mathieu

2005-01-01

We present in this paper a symbol recognition system for the graphic documents. This one is based on a contextual approach for symbol structural recognition exploiting an Object-Process Methodology. It uses a processing library composed of structural recognition processings and contextual evaluation processings. These processings allow our system to deal with the multi-representation of symbols. The different processings are controlled, in an automatic way, by an inference engine during the r...

Short communication: QTL mapping for ear tip-barrenness in maize

Energy Technology Data Exchange (ETDEWEB)

Ding, J.; Ma, J.; Chen, J.; Ai, T.; Li, Z.; Tian, Z.; Wu, S.; Chen, W.; Wu, J.

2016-11-01

Barren tip on corn ear is an important agronomic trait in maize, which is highly associated with grain yield. Understanding the genetic basis of tip-barrenness may help to reduce the ear tip-barrenness in breeding programs. In this study, ear tip-barrenness was evaluated in two environments in a F2:3 population, and it showed significant genotypic variation for ear tip-barrenness in both environments. Using mixed-model composite interval mapping method, three additive effects quantitative trait loci (QTL) for ear tip-barrenness were mapped on chromosomes 2, 3 and 6, respectively. They explained 16.6% of the phenotypic variation, and no significant QTL × Environment interactions and digenic interactions were detected. The results indicated that additive effect was the main genetic basis for ear tip-barrenness in maize. This is the first report of QTL mapped for ear tip-barrenness in maize. (Author)

User-independent accelerometer-based gesture recognition for mobile devices

Directory of Open Access Journals (Sweden)

Eduardo METOLA

2013-07-01

Full Text Available Many mobile devices embed nowadays inertial sensors. This enables new forms of human-computer interaction through the use of gestures (movements performed with the mobile device as a way of communication. This paper presents an accelerometer-based gesture recognition system for mobile devices which is able to recognize a collection of 10 different hand gestures. The system was conceived to be light and to operate in a user-independent manner in real time. The recognition system was implemented in a smart phone and evaluated through a collection of user tests, which showed a recognition accuracy similar to other state-of-the art techniques and a lower computational complexity. The system was also used to build a human-robot interface that enables controlling a wheeled robot with the gestures made with the mobile phone

2.5D Multi-View Gait Recognition Based on Point Cloud Registration

Science.gov (United States)

Tang, Jin; Luo, Jian; Tjahjadi, Tardi; Gao, Yan

2014-01-01

This paper presents a method for modeling a 2.5-dimensional (2.5D) human body and extracting the gait features for identifying the human subject. To achieve view-invariant gait recognition, a multi-view synthesizing method based on point cloud registration (MVSM) to generate multi-view training galleries is proposed. The concept of a density and curvature-based Color Gait Curvature Image is introduced to map 2.5D data onto a 2D space to enable data dimension reduction by discrete cosine transform and 2D principle component analysis. Gait recognition is achieved via a 2.5D view-invariant gait recognition method based on point cloud registration. Experimental results on the in-house database captured by a Microsoft Kinect camera show a significant performance gain when using MVSM. PMID:24686727

Accuracy of MFCC-Based Speaker Recognition in Series 60 Device

Directory of Open Access Journals (Sweden)

Pasi Fränti

2005-10-01

Full Text Available A fixed point implementation of speaker recognition based on MFCC signal processing is considered. We analyze the numerical error of the MFCC and its effect on the recognition accuracy. Techniques to reduce the information loss in a converted fixed point implementation are introduced. We increase the signal processing accuracy by adjusting the ratio of presentation accuracy of the operators and the signal. The signal processing error is found out to be more important to the speaker recognition accuracy than the error in the classification algorithm. The results are verified by applying the alternative technique to speech data. We also discuss the specific programming requirements set up by the Symbian and Series 60.

Study on recognition algorithm for paper currency numbers based on neural network

Science.gov (United States)

Li, Xiuyan; Liu, Tiegen; Li, Yuanyao; Zhang, Zhongchuan; Deng, Shichao

2008-12-01

Based on the unique characteristic, the paper currency numbers can be put into record and the automatic identification equipment for paper currency numbers is supplied to currency circulation market in order to provide convenience for financial sectors to trace the fiduciary circulation socially and provide effective supervision on paper currency. Simultaneously it is favorable for identifying forged notes, blacklisting the forged notes numbers and solving the major social problems, such as armor cash carrier robbery, money laundering. For the purpose of recognizing the paper currency numbers, a recognition algorithm based on neural network is presented in the paper. Number lines in original paper currency images can be draw out through image processing, such as image de-noising, skew correction, segmentation, and image normalization. According to the different characteristics between digits and letters in serial number, two kinds of classifiers are designed. With the characteristics of associative memory, optimization-compute and rapid convergence, the Discrete Hopfield Neural Network (DHNN) is utilized to recognize the letters; with the characteristics of simple structure, quick learning and global optimum, the Radial-Basis Function Neural Network (RBFNN) is adopted to identify the digits. Then the final recognition results are obtained by combining the two kinds of recognition results in regular sequence. Through the simulation tests, it is confirmed by simulation results that the recognition algorithm of combination of two kinds of recognition methods has such advantages as high recognition rate and faster recognition simultaneously, which is worthy of broad application prospect.

Noisy Ocular Recognition Based on Three Convolutional Neural Networks

Directory of Open Access Journals (Sweden)

Min Beom Lee

2017-12-01

Full Text Available In recent years, the iris recognition system has been gaining increasing acceptance for applications such as access control and smartphone security. When the images of the iris are obtained under unconstrained conditions, an issue of undermined quality is caused by optical and motion blur, off-angle view (the user’s eyes looking somewhere else, not into the front of the camera, specular reflection (SR and other factors. Such noisy iris images increase intra-individual variations and, as a result, reduce the accuracy of iris recognition. A typical iris recognition system requires a near-infrared (NIR illuminator along with an NIR camera, which are larger and more expensive than fingerprint recognition equipment. Hence, many studies have proposed methods of using iris images captured by a visible light camera without the need for an additional illuminator. In this research, we propose a new recognition method for noisy iris and ocular images by using one iris and two periocular regions, based on three convolutional neural networks (CNNs. Experiments were conducted by using the noisy iris challenge evaluation-part II (NICE.II training dataset (selected from the university of Beira iris (UBIRIS.v2 database, mobile iris challenge evaluation (MICHE database, and institute of automation of Chinese academy of sciences (CASIA-Iris-Distance database. As a result, the method proposed by this study outperformed previous methods.

Noisy Ocular Recognition Based on Three Convolutional Neural Networks.

Science.gov (United States)

Lee, Min Beom; Hong, Hyung Gil; Park, Kang Ryoung

2017-12-17

In recent years, the iris recognition system has been gaining increasing acceptance for applications such as access control and smartphone security. When the images of the iris are obtained under unconstrained conditions, an issue of undermined quality is caused by optical and motion blur, off-angle view (the user's eyes looking somewhere else, not into the front of the camera), specular reflection (SR) and other factors. Such noisy iris images increase intra-individual variations and, as a result, reduce the accuracy of iris recognition. A typical iris recognition system requires a near-infrared (NIR) illuminator along with an NIR camera, which are larger and more expensive than fingerprint recognition equipment. Hence, many studies have proposed methods of using iris images captured by a visible light camera without the need for an additional illuminator. In this research, we propose a new recognition method for noisy iris and ocular images by using one iris and two periocular regions, based on three convolutional neural networks (CNNs). Experiments were conducted by using the noisy iris challenge evaluation-part II (NICE.II) training dataset (selected from the university of Beira iris (UBIRIS).v2 database), mobile iris challenge evaluation (MICHE) database, and institute of automation of Chinese academy of sciences (CASIA)-Iris-Distance database. As a result, the method proposed by this study outperformed previous methods.

Human body contour data based activity recognition.

Science.gov (United States)

Myagmarbayar, Nergui; Yuki, Yoshida; Imamoglu, Nevrez; Gonzalez, Jose; Otake, Mihoko; Yu, Wenwei

2013-01-01

This research work is aimed to develop autonomous bio-monitoring mobile robots, which are capable of tracking and measuring patients' motions, recognizing the patients' behavior based on observation data, and providing calling for medical personnel in emergency situations in home environment. The robots to be developed will bring about cost-effective, safe and easier at-home rehabilitation to most motor-function impaired patients (MIPs). In our previous research, a full framework was established towards this research goal. In this research, we aimed at improving the human activity recognition by using contour data of the tracked human subject extracted from the depth images as the signal source, instead of the lower limb joint angle data used in the previous research, which are more likely to be affected by the motion of the robot and human subjects. Several geometric parameters, such as, the ratio of height to weight of the tracked human subject, and distance (pixels) between centroid points of upper and lower parts of human body, were calculated from the contour data, and used as the features for the activity recognition. A Hidden Markov Model (HMM) is employed to classify different human activities from the features. Experimental results showed that the human activity recognition could be achieved with a high correct rate.

Facial expression recognition based on improved local ternary pattern and stacked auto-encoder

Science.gov (United States)

Wu, Yao; Qiu, Weigen

2017-08-01

In order to enhance the robustness of facial expression recognition, we propose a method of facial expression recognition based on improved Local Ternary Pattern (LTP) combined with Stacked Auto-Encoder (SAE). This method uses the improved LTP extraction feature, and then uses the improved depth belief network as the detector and classifier to extract the LTP feature. The combination of LTP and improved deep belief network is realized in facial expression recognition. The recognition rate on CK+ databases has improved significantly.

Bacteriology of chronic discharging ears in Port Harcourt, Nigeria ...

African Journals Online (AJOL)

Methods: Ear swabs of discharging ears aseptically collected from 102 patients of various age groups attending Ear, Nose, and Throat out-patient clinic at University of Port Harcourt Teaching Hospital were cultured for bacterial agents using blood agar, chocolate agar and MacConkey agar. Culture plates were incubated ...

Method for secure electronic voting system: face recognition based approach

Science.gov (United States)

Alim, M. Affan; Baig, Misbah M.; Mehboob, Shahzain; Naseem, Imran

2017-06-01

In this paper, we propose a framework for low cost secure electronic voting system based on face recognition. Essentially Local Binary Pattern (LBP) is used for face feature characterization in texture format followed by chi-square distribution is used for image classification. Two parallel systems are developed based on smart phone and web applications for face learning and verification modules. The proposed system has two tire security levels by using person ID followed by face verification. Essentially class specific threshold is associated for controlling the security level of face verification. Our system is evaluated three standard databases and one real home based database and achieve the satisfactory recognition accuracies. Consequently our propose system provides secure, hassle free voting system and less intrusive compare with other biometrics.

Face sketch recognition based on edge enhancement via deep learning

Science.gov (United States)

Xie, Zhenzhu; Yang, Fumeng; Zhang, Yuming; Wu, Congzhong

2017-11-01

In this paper,we address the face sketch recognition problem. Firstly, we utilize the eigenface algorithm to convert a sketch image into a synthesized sketch face image. Subsequently, considering the low-level vision problem in synthesized face sketch image .Super resolution reconstruction algorithm based on CNN(convolutional neural network) is employed to improve the visual effect. To be specific, we uses a lightweight super-resolution structure to learn a residual mapping instead of directly mapping the feature maps from the low-level space to high-level patch representations, which making the networks are easier to optimize and have lower computational complexity. Finally, we adopt LDA(Linear Discriminant Analysis) algorithm to realize face sketch recognition on synthesized face image before super resolution and after respectively. Extensive experiments on the face sketch database(CUFS) from CUHK demonstrate that the recognition rate of SVM(Support Vector Machine) algorithm improves from 65% to 69% and the recognition rate of LDA(Linear Discriminant Analysis) algorithm improves from 69% to 75%.What'more,the synthesized face image after super resolution can not only better describer image details such as hair ,nose and mouth etc, but also improve the recognition accuracy effectively.

Preoperative diagnosis and surgical strategy in congenital auditory ossicular malformation of 26 ears

International Nuclear Information System (INIS)

Kanazawa, Yuji; Naito, Yasushi; Shinohara, Shogo; Fujiwara, Keizo; Kikuchi, Masahiro; Yamazaki, Hiroshi; Kurihara, Risa; Kishimoto, Ippei

2012-01-01

We retrospectively analyzed 26 ears of 21 subjects having auditory ossicular malformation and who had undergone auditory reconstruction between April 2004 and December 2010 at our clinic. We checked preoperative condition, pathological classification, surgical procedure, and hearing improvement. We could predict pathological conditions precisely from preoperative computed tomography (CT), including incudostapedial disconnection (9/12, 75%) and malleus and/or incus fixation (7/12, 58%), which tended to be present in external ear malformation, and stapes footplate fixation (0/12, 0%). We could not, however, predict complex malformation (0/8, 0%). Overall success was 90% (18/20) in the 20 ears observed for at least 1 year. In the 2 ears without improved hearing, the first had congenital cholesteatoma and no stapes superstructure, was treated with type IV tympanoplasty. The second had malleus, incus, and stapes fixation and discontinuity between the incus and stapes, and was treated with type III tympanoplasty and stapes mobilization. Preoperative diagnosis is difficult in mixed congenital auditory ossicular malformation, especially stapes footplate fixation, possibly requiring unexpected procedures, with a poor hearing outcome. Preoperative status must thus be evaluated precisely using hearing, tympanometry, acoustic reflex test, and CT. Temporal bone CT and external ear findings are useful in diagnosing middle-ear malformation. Subjects' informed consent should also be obtained due to the possible need for changing procedure based on findings during surgery. (author)

Locality constrained joint dynamic sparse representation for local matching based face recognition.

Science.gov (United States)

Wang, Jianzhong; Yi, Yugen; Zhou, Wei; Shi, Yanjiao; Qi, Miao; Zhang, Ming; Zhang, Baoxue; Kong, Jun

2014-01-01

Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC) in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW) demonstrate the effectiveness of LCJDSRC.

Locality constrained joint dynamic sparse representation for local matching based face recognition.

Directory of Open Access Journals (Sweden)

Jianzhong Wang

Full Text Available Recently, Sparse Representation-based Classification (SRC has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW demonstrate the effectiveness of LCJDSRC.

Possibility of object recognition using Altera's model based design approach

International Nuclear Information System (INIS)

Tickle, A J; Harvey, P K; Smith, J S; Wu, F

2009-01-01

Object recognition is an image processing task of finding a given object in a selected image or video sequence. Object recognition can be divided into two areas: one of these is decision-theoretic and deals with patterns described by quantitative descriptors, for example such as length, area, shape and texture. With this Graphical User Interface Circuitry (GUIC) methodology employed here being relatively new for object recognition systems, the aim of this work is to identify if the developed circuitry can detect certain shapes or strings within the target image. A much smaller reference image feeds the preset data for identification, tests are conducted for both binary and greyscale and the additional mathematical morphology to highlight the area within the target image with the object(s) are located is also presented. This then provides proof that basic recognition methods are valid and would allow the progression to developing decision-theoretical and learning based approaches using GUICs for use in multidisciplinary tasks.