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检索条件"任意字段=3rd Iberian Conference on Pattern Recognition and Image Analysis"

共 1490 条记录，以下是361-370 订阅

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Workshop 1: First Workshop on Information Technologies for Kestenberg Movement Profile analysis: An Early Stage Developmental Disorder Detection Case

Workshop 1: First Workshop on Information Technologies for K...

引用

International conference on Informatics, Electronics & Vision (ICIEV)

作者： Yukari Sakiyama Haruhiko Takase Hiroharu Kawanaka Mukogawa Women's University Japan Mie University Japan

This workshop is organized to study matters of Kestenberg Movement Profile analysis (aims, methods, societies, etc.) and its IT support. The relevant specialists, especially related to the dance/movement therapy and the computer & electrical engineering should participate. This should consist of some hands-on tutorial and panel discussion. This workshop is primarily organized as a part of the research project funded by JSPS: “an early stage (baby & toddler) developmental disorder detection using KMP analysis and its IT support”.

关键词： conferences Medical treatment Pediatrics Lead Neural networks image processing Biomedical imaging

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Approaches on Partial Face recognition: A Literature Review

Approaches on Partial Face Recognition: A Literature Review

引用

International conference on Trends in Electronics and Informatics (ICEI)

作者： M R Reshma B Kannan Department of Computer Applications Cochin University of Science and Technology Kochi Kerala India

Face recognition technology has gained attention over past years owing to its broad applications. It is a potential research area in the scope of image analysis, computer vision and pattern recognition. The requirement of identifying an authentic user through different authentication mechanisms are increasing rapidly following the intense concerns about security, and rapid advancement in networking, communication, and mobility. Face recognition is an area which has attained attention over the last few decades. The traditional applications of face recognition system, especially those used for access control, authentication, and surveillance, usually need maximum information of face to attain exceptional performance in recognition. Occasionally it is difficult to get access of a full face under certain restricted situations. For example, a non-cooperative face can lead to face occlusion. For recognizing an arbitrary image captured in an unconstrained environment is a more challenging condition in video surveillance, handheld devices etc. Numerous methods have been devised for unconstrained face recognition with remarkable achievements. This paper provides an overview of different partial face recognition approaches proposed.

关键词： Face Face recognition Feature extraction image recognition Surveillance conferences Market research

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Inspection of IC wafer Defects Based on image Registration 3

Inspection of IC wafer Defects Based on Image Registration

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3rd IEEE Advanced Information Technology, Electronic and Automation Control conference (IAEAC)

作者： Liu, Xifeng Hu, Yuwei Beijing Instrument Ind Res Inst Beijing Peoples R China

ISBN: (纸本)9781538645093

An automatic integrated circuit (IC) wafer inspection system based on image registration has been developed. This inspection system addresses the task of detection the key defects on the surface of IC wafer. It introduces the method of Speeded Up Robust Features (SURF) image registration. The algorithm is used to achieve the alignment of space position between the standard image and the detected image. Defect feature extraction and analysis techniques are studied regarding the characteristics of detected images of IC wafer. The contour extraction with pattern recognition was applied to classify the defects. This method classify the type of defects based on the number in the Boundary Contour and material increase or decrease. The effectiveness of the method is demonstrated through some samples of IC wafer.

关键词： image registration SURF integrated circuit (IC) wafer inspection

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Comparison of principal component analysis algorithm and local binary pattern for feature extraction on face recognition system 3

Comparison of principal component analysis algorithm and loc...

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3rd Annual Applied Science and Engineering conference (AASEC)

作者： Taufik, Ichsan Musthopa, Maya Atmadja, Aldy Rialdy Ramdhani, Muhammad Ali Gerhana, Yana Aditia Ismail, Nanang UIN Sunan Gunung Djati Bandung Informat Dept Fac Sci & Technol Bandung Indonesia UIN Sunan Gunung Djati Bandung Elect Engn Dept Fac Sci & Technol Bandung Indonesia

Characteristic extraction in face recognition is a step to get characteristic information from the image. The characteristic extraction algorithm is tested against several scenarios of different sunlight and lights, objects facing the camera and not facing the camera. The sample test data were performed on 4 people using a video file or frame numbering 70 for recognizable faces using Principal Component analysis (PCA) and Local Binary pattern (LBP) algorithms. The result of the research shows that Local Binary pattern (LBP) algorithm in object scenario facing camera with sunlighting in room has accuracy of 98.59%, recognition time of 812,817 milliseconds, FAR of 1,41% and FRR of 0%, while at Principal Component analysis (PCA) 98.59% accuracy, recognition time of 1275,761 milliseconds, FAR of 1.41% and FRR of 0%. Based on these results, the Local Binary pattern (LBP) algorithm is more efficient than Principal Component analysis (PCA) for face recognition of the scenarios to be implemented in real-time video.

关键词： Local binary pattern

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Human Age Classification System Using K-NN Classifier 3rd

Human Age Classification System Using K-NN Classifier

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3rd International conference on Advanced Informatics for Computing Research (ICAICR)

作者： Priyadarshni, Vaishnawi Nayyar, Anand Solanki, Arun Anuragi, Archana Gautam Buddha Univ Dept Comp Sci & Engn Greater Noida India Duy Tan Univ Grad Sch Da Nang Vietnam Govt Girls Polytech Dept Comp Sci Charkhari Mahoba India

ISBN: (纸本)9789811501081;9789811501074

The age classification system is used to categorize age into various groups determined by facial features. Many researchers have used different techniques for the age classification system, namely Geometric Ratio, Wrinkle Ratio, Local Gabor pattern, Histograms of Oriented Gradients, Adaptive Neuro-Fuzzy Inference system, Texture feature, Support Vector Machine and Artificial neural network. The current system does not give great precision in light of the fact that these strategies are wasteful for classification. The proposed work represents the classification of images depending on the groups. This work classifies the age into old, adult and child groups. This work completes in three steps, i.e., preprocessing, facial aging feature extraction and classification. In preprocessing, the RGB image is converted into a grayscale level image;the facial aging feature extraction is performed by skin texture feature extraction and wrinkle analysis. LGBPH and the density of wrinkles accomplished the wrinkle analysis. LGBPH is a histogram of LGBP which is calculated by LBP. The LGBP feature is not dynamic for features like rotation, alignment, and the illumination of the image. The proposed work selected three different skins for skin texture feature and five different skin textures for wrinkle investigation. This work uses K-NN classifier due to its fast processing;classifies the testing dataset from training dataset. The LGBPH provides better results and estimates the accuracy as compared to the previous technique used by the researcher. This classification is a triumphant work as it gives an efficient classification using facial aging feature extraction.

关键词： Age classification system Facial aging feature extraction K-Nearest Neighbor (K-NN) Local Gabor Binary pattern Histogram (LGBPH) Wrinkle analysis

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WEB-technology for Medical images Segmentation 3

WEB-technology for Medical Images Segmentation

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3rd Russian-Pacific conference on Computer Technology and Applications (RPC)

作者： Doronicheva, Anna V. Savin, Sergey Z. Russian Acad Sci Far Eastern Branch Ctr Comp Fed State Budgetary Inst Sci Khabarovsk Russia

ISBN: (纸本)9781538675311

In work is described practical using of WEB-technology for segmentation and analysis tasks of medical image. Progress in the development of bioinformatics and mathematical methods in biomedicine, as well as the development of computer and telecommunications systems and networks determines the look of the present and future of medical technology and of medicine in general [8, 10]. At last years of one of the directions of development of cloud, computing technologies in high-tech-medicine is a processing the digital image: improvement of quality of image, recovering image, its recognition of separate elements. recognition of pathological processes is one of the most important problems of processing the medical image. By now, a number of standards for medical imaging have been developed. By analogy with CAD/CAM systems (computer aided design and computer aided manufacturing) for technical applications, CAD (computer-aided diagnosis) systems are being developed for medical purposes. Some of them are already successfully operating, but to date these systems are only "assistants" of a diagnostician who takes decisions. CAD algorithms for medical imaging systems typically include image segmentation, the selection of some objects of interest ("masses"), their analysis, parametric description of the selected objects and their classification.

关键词： expert system computer-aided diagnosis (CAD) pattern recognition medical image scintigraphy

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Facial Expression recognition Based on G-2DPCA Feature and Sparse Representation Classification 3

Facial Expression Recognition Based on G-2DPCA Feature and S...

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IEEE 3rd International conference on Signal and image Processing (ICSIP)

作者： Wang, Yan Li, Ming Zhang, Congxuan Chen, Hao Nanchang Hangkong Univ Key Lab Jiangxi Prov Image Proc & Pattern Recogni Nanchang Jiangxi Peoples R China Nanchang Hangkong Univ Engn Training Ctr Nanchang Jiangxi Peoples R China

ISBN: (纸本)9781538663967

In this paper, we proposed an effective method of facial expression recognition based on a G-2DPCA feature and Sparse Representation-based Classification (SRC). Gabor filters with five scales and eight directions are first employed for feature extraction. To address the high dimension of Gabor features, we select one out of forty Gabor filters with an optimal parameter pair of scales and directions to filter facial images. Two-dimensional principal component analysis (2DPCA) is utilized for image representation and data dimension reduction. It retains the 2D geometric structure of an image, and the image matrix does not need to transform into a vector, which reducing the computation time greatly. Finally, Gabor plus 2DPCA (G-2PCA) features are regarded as the atoms of dictionary in SRC. Experimental results demonstrate that the proposed method has better performance than the existing algorithms.

关键词： facial expression recognition Gabor wavelet 2DPCA SRC

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Automatic Medicinal Plants Classification using Multi-channel Modified Local Gradient pattern with SVM Classifier

Automatic Medicinal Plants Classification using Multi-channe...

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International conference on Informatics, Electronics & Vision (ICIEV)

作者： Umme Habiba Md. Rasel Howlader Md. Aminul Islam Rahat Hossain Faisal Md. Mostafijur Rahman Dept. of Computer Science and Engineering University of Barisal Barisal Bangladesh

Most of the people in the world rely on traditional medicine which is made from medicinal plants. However, very few works concentrate on automatic classification. Therefore, the automatic classification of medicinal plants demands more investigation which is an important issue for conservation, authentication, and production of medicines. In this paper, for automatically classifying medicinal plants, we present a Multi-channel Modified Local Gradient pattern (MCMLGP), a new texture-based feature descriptor that uses different channels of color images for extracting more significant features to improve the performance of classification. We have trained our proposed approach using SVM classifier with various kernels such as linear, polynomial and HI. In addition, we have used different feature descriptors for comparative experimental analysis with MCMLGP by conducting the rigorous experiment on our own medicinal plants dataset. The proposed approach gain higher accuracy (96.11%) than other techniques, and significantly valuable for exploration and evolution of medicinal plants classification.

关键词： Biomedical imaging Feature extraction image color analysis Support vector machines Kernel Harmonic analysis Histograms

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image Inpainting Method Based on Mixed Median

Image Inpainting Method Based on Mixed Median

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International conference on Informatics, Electronics & Vision (ICIEV)

作者： Dang N. H. Thanh V. B. Surya Prasath Le Minh Hieu Hiroharu Kawanaka Department of Information Technology Hue College of Industry Hue VN Department of Electrical Engineering and Computer Science University of Cincinnati OH USA Department of Economics The University of Danang VN Department of Electrical and Electronic Engineering Mie University Mie Japan

The image inpainting is an interesting problem of image processing that has wide range of application in science, engineering, medicine and other fields of life. The inpainting is a process to fill the corrupted or missing parts of images. So, the image inpainting can be used in various cases, such as restoration of corrupted images, removal of unnecessary objects on images to improve quality of postprocessing tasks, image zooming etc. In this paper, we propose an image inpainting method based on mixed median. The mixed median proposed here is a combination of two kinds of median of pixels intensity: median of uncorrupted pixels in a clipping window and median of the maximum repetitive pixel values. In the experiment, we handle the test on the open dataset with given masks to generate the corrupted regions. This method is helpful to assess the inpainting quality based on the peak signal-to-noise ratio and the structure similarity metrics. We also compare the proposed method with the harmonic inpainting method to prove its own effectiveness.

关键词： image restoration Harmonic analysis Power harmonic filters Measurement image quality Wiener filters

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Uneven Illumination Compensation for Unconstrained Face recognition Using LBP 3

Uneven Illumination Compensation for Unconstrained Face Reco...

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3rd International conference for Convergence in Technology (I2CT)

作者： Dandpat, Swarup Kumar Meher, Sukadev Bopche, Vivek Natl Inst Technol Dept Elect & Commun Engn Rourkela 768009 India

ISBN: (纸本)9781538642733

Face recognition results are degraded when the test image is having nonuniform illumination variations. Due to the lighting variations, different expressions and occlusions the facial appearance of the face changes dramatically such that recognition by the methods is quite a difficult task. Out of which the problems due to illumination variations such as shadows, under lighting, over lighting in the face are the crucial problems which are to be overcome to achieve the satisfactory results for an automatic face recognition system. In this paper, we propose an efficient illumination compensation method based on frequency analysis and multi-resolution analysis. The effect of uneven lighting variations of the test image is efficiently and effectively removed by applying the LBP image to modify the magnitude information in the frequency domain. The magnitudes of the LBP image compensate the distorted magnitudes of the original image, caused by the light variations, as well as add some structural information to the restored image. To examine the efficacy of our developed method, histogram equalization based normalization and Fourier based normalization methods are compared with the proposed method. An extensive simulation study has been carried out to measure the effectiveness of our proposed method on the images containing extreme illumination variations. For this purpose, we have used the Extended Yale-B face database. From the results, it is found that our proposed method outperforms other methods and also it works better for extremely poor illuminated images.

关键词： Face recognition Discrete Fourier Transform Local Binary pattern Illumination Normalization Feature Extraction

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