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检索条件"任意字段=5th International Symposium on Multispectral Image Processing and Pattern Recognition"

共 1596 条记录，以下是1481-1490 订阅

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Facial Expression recognition with LDPP & LTP using Deep Belief Network

Facial Expression Recognition with LDPP & LTP using Deep Bel...

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international Conference on Signal processing and Integrated Networks (SPIN)

作者： Vasudha Deepti Kakkar Department of Electronics and Communication Engineering Dr. B.R. Ambedkar National Institute of Technology Jalandhar India

In this paper, local directional position pattern (LDPP) and local ternary pattern (LTP) are selected for facial recognition method which are having many advantages over previous techniques like local binary pattern (LBP) and local directional pattern (LDP). the selected techniques of LDPP and LTP are estrangement in their algorithms which help solely to extract features out of an image. LDPP is a revised form of LDP. In a typical LDP, only the top edge direction was taken into consideration, but strength sign of the pixel was not considered which may result in same code for opposite kind of edge pixel. this snag is overcome by LDPP which is further concatenated with LTP for better feature extraction. Once features are extracted they are trained using deep belief network. In the experimental work 10 images of each expression i.e. angry, surprise, disgust, neutral, sad, smile are selected. LDPP and LTP are concatenated followed by principal component analysis (PCA) and general discriminant analysis (GDA). Further for training, Deep Belief Network (DBN) is used which eventually increases the recognition rate and achieve accuracy of 95.3% which was 89.3% without concatenating.

关键词： Feature extraction image edge detection Principal component analysis Face Face recognition Training

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Rotational symmetry in CBED patterns

Rotational symmetry in CBED patterns

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international Conference on Signal processing Proceedings (ICSP)

作者： Qingfeng Yu Guobin Hu Hanqing Lu Lianmao Peng National Lab of Pattern Recognition and Beijing Laboratory of Electron Microscopy CAS Chinese Academy and Sciences China

A method for efficient detection of the dominant local rotational symmetry in grey level images of CBED patterns is described. the general approach is to define a local measure of rotational symmetry that transforms the symmetry detection problem to an optimization problem, and obtain the symmetric regions by an efficient global optimization algorithm. In this paper, we present the correlation function as the measure of rotational symmetry. the value depends on the center of the supporting region, its size, and the rotational angle. the genetic algorithm is taken to search the global maximum of the rotational symmetry. the method is shown in experiments to be both effective and quick.

关键词： Rotation measurement image edge detection Genetic algorithms Electron beams image analysis Shape pattern recognition Laboratories Electron microscopy Content addressable storage

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Tomato Ripeness Clustering Using 6-Means Algorithm Based on V-Channel Otsu Segmentation 5

Tomato Ripeness Clustering Using 6-Means Algorithm Based on ...

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5th international symposium on Computational and Business Intelligence (ISCBI)

作者： Sari, Yuita Arum Adinugroho, Sigit Brawijaya Univ Fac Comp Sci Comp Vis Res Grp Malang Indonesia

ISBN: (纸本)9781538617724

Segmentation process in an essential part in image processing to obtain good preparation either for further process of data mining or object recognition. this paper proposes a new method of segmenting tomato image for clustering its ripeness. the tomato images are taken from three types of smartphone camera in various lighting condition with white background. When taking picture by using smartphone camera, the image is a bit darker or lighter in certain side, so the segmentation is involved to the following stage. Color transformation is needed at the first stage of preprocessing which converts RGB channel to YUV channel in order to apply histogram equalization. YUV is better to perceptual similarities in machine vision than RGB. Histogram equalization is applied in single Y channel of an image. Afterwards merge a V channel to YUV channel then transform it to RGB color model to observe the difference and convert it back to YUV for segmentation. Otsu combined with V channel thresholding is utilized to segment image better. To evaluate the segmentation performance, clustering method is computed based on retrieved color of segmented image using K-Means, in which k=6 because of there are 6 stages of tomato ripeness. Color feature extraction by means of R, G, a*, and b* color channel are treated subsequently. Experimental results show the system yield 1% Mean Square Error in clustering the ripeness of tomatoes.

关键词： tomato clustering image processing segmentation

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Characterizing the Role of a Single Coupling Layer in Affine Normalizing Flows 1

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42nd German Conference on pattern recognition, DAGM GCPR 2020 held in parallel with 25th international symposium on Vision, Modeling, and Visualization, VMV 2020 and 10th Eurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2020

作者： Draxler, Felix Schwarz, Jonathan Schnörr, Christoph Köthe, Ullrich Heidelberg Collaboratory for Image Processing Heidelberg University Heidelberg Germany Visual Learning Lab Heidelberg University Heidelberg Germany Image and Pattern Analysis Group Heidelberg University Heidelberg Germany

ISBN: (数字)9783030712785

ISBN: (纸本)9783030712778

Deep Affine Normalizing Flows are efficient and powerful models for high-dimensional density estimation and sample generation. Yet little is known about how they succeed in approximating complex distributions, given the seemingly limited expressiveness of individual affine layers. In this work, we take a first step towards theoretical understanding by analyzing the behaviour of a single affine coupling layer under maximum likelihood loss. We show that such a layer estimates and normalizes conditional moments of the data distribution, and derive a tight lower bound on the loss depending on the orthogonal transformation of the data before the affine coupling. this bound can be used to identify the optimal orthogonal transform, yielding a layer-wise training algorithm for deep affine flows. Toy examples confirm our findings and stimulate further research by highlighting the remaining gap between layer-wise and end-to-end training of deep affine flows. © 2021, Springer Nature Switzerland AG.

关键词： Maximum likelihood estimation

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A structural features based segmentation for off-line handwritten Arabic text

A structural features based segmentation for off-line handwr...

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international symposium on I/V Communications and Mobile Network (ISVC)

作者： Moftah Elzobi Ayoub Al-Hamadi Laslo Dinges Bernd Michaelis Institute of Electronics Signal Processing and Communications Otto-von-Guericke University of Magdeburg Magdeburg Germany

Automatic Arabic handwritten text recognition is still an open research field, methods that describe satisfactory solution are still lacking. this can be attributed to cursive orthography and to the letter shape context sensitivity, which complex the problem of the character segmentation. this paper presents a heuristic rule based analytical segmentation approach for handwritten Arabic text, which preceded by a pre-process phase that handles binarization, short gaps closing, skew estimation, and critical features points calculation. Unlike other approaches a broader set of candidates for segmentation is generated and multi phase election process is performed to elect the best suitable candidates. Experiments are conducted on a database of 50 images of text sentences with an average of 4 words. Results were very satisfactory and outperform literature documented results.

关键词： image segmentation Pixel Character recognition Feature extraction Text recognition Handwriting recognition image recognition

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RBF based receivers for DS-CDMA with reduced complexity

RBF based receivers for DS-CDMA with reduced complexity

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IEEE international symposium on Spread Spectrum Techniques and Applications

作者： R. Tanner D.G.M. Cruickshank Department of Electronics and Electrical Engineering Signals & Systems Group University of Edinburgh Edinburgh UK

this paper presents a Mahalanobis based radial basis function network (RBF) receiver structure with reduced complexity. It is also illustrated, how the RBF receiver could be employed as a multiuser detector. the RBF structure has superior performance over linear receiver structures and is equivalent to MLSD in an AWGN channel. However, a drawback is its complexity in multipath channels. Ideas from pattern recognition are exploited to reduce its complexity for multipath scenarios with little performance loss.

关键词： Multiaccess communication Signal processing Detectors Multipath channels Multiuser detection Neural networks Maximum likelihood detection Buildings AWGN channels pattern recognition

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Comparison of k-NN, SVM, and NN in Pit pattern Classification of Zoom-Endoscopic Colon images using Co-Occurrence Histograms

Comparison of k-NN, SVM, and NN in Pit Pattern Classificatio...

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international symposium on image and Signal processing and Analysis

作者： M. Hafner A. Gangl F. Wrba K. thonhauser H.-P. Schmidt Ch. Kastinger A. Uhl A. Vecsei Vienna Medical University Austria Salzburg University Austria Carinthia Tech Institute Klagenfurt Austria Saint Anna Children's Hospital Austria

ISBN: (纸本)9531841160;97

Co-occurrence histograms are used as features to classify magnifying endoscope imagery with k-NN, SVM, and NN classifiers. In the k-NN classification case these histograms may improve the classification accuracy of simple ID color histograms up to 10% in the 2 classes case and up to 5% in the 6 classes case. the classification results of SVM and NN classifiers have turned out to be noncompetitive and do not improve the classification result of ID color histograms.

关键词： Support vector machines Support vector machine classification Neural networks pattern classification Colon Histograms Lesions Endoscopes Cancer Colonoscopy

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Bag of Facial Components: A Data Enrichment Approach for Face image processing

Bag of Facial Components: A Data Enrichment Approach for Fac...

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international Conference of Advanced Informatics: Concept, theory and Application (ICAICTA)

作者： Iping Supriana Suwardi Achmad Imam Kistijantoro Tjokorda Agung Budi Wirayuda Ginar Santika Niwanputri School of Electrical Engineering and Informatics Institut Teknologi Bandung

ISBN: (纸本)9781538648056

Facial images are one of the raw data that can be processed to produce various information/representations, especially for computer vision, pattern recognition, and biometrics. Moreover, identity recognition, expression recognition and visitor demographic calculations are applications that can be generated through the processing of facial images. In order to perform face image processing, a face detection mechanism is needed to isolate the face area (region-of-interest-ROI). Previous research generally views facial images as unity for further processing with feature extraction techniques and recognition. this paper proposes post-processing from face detection (Viola-Jones based) to produce a bag of facial components as a data representation for the next processes which are feature extraction and recognition. the post-processing is done based on the geometric rules of the face and golden ratio to produce more accurate detection. From the experiment, the proposed method achieves 96.88% of accuracy on the development part whilst the accuracy of testing part reaches 92.52% (with precision 95.32% and recall 96.62%).

关键词： computer vision emotion recognition face recognition feature extraction Mug shots Feature extraction Facial recognition emotion recognition images computer vision Bag device Face Face Representation of data PURSE Golden ratio image processing

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Transparency quantification. Application to composite materials quality controls by image processing 5th

Transparency quantification. Application to composite materi...

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5th international Conference on Computer Analysis of images and patterns, CAIP 1993

作者： Bres, S. Emptoz, H. Merle, G. LISPI Equipe de Reconnaissance de formes et Diagnostic I.N.S.A Bat 403 20 Avenue A. Einstein VilleurbanneCedex69621 France Laboratoire des Matériaux Macromoléculaires I.N.S.A Bat 403 20 Avenue A. Einstein Villeurbanne Cedex69621 France

ISBN: (纸本)9783540572336

A piece in composite material is composed of a frame, or reinforcement, in fibres put together with a resin. the quality of such a piece depends directly an the quality with which the resin penetrates the fibres of the frame. So it is interesting to be able to quantify the evolution of the impregnation quality during the fabrication. this article and the quality controls it describes concern glass fibres reinforcements. At the beginning, and without resin, this kind of reinforcement is white and opaque. It becomes transparent as the impregnation by the resin increases. A good way to quantify the impregnation level is to correlate it to the transparency level. For this purpose, we take images of the material during the manufacturing phase, and we treat each of them to extract an impregnation level. this operation will give us impregnation curves. © 1993, Springer Verlag. All rights reserved.

关键词： Resins

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Scale Space and PDE Methods in Computer Vision 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Ron Kimmel Nir A. Sochen Joachim Weickert

ISBN: (数字)9783540320128

ISBN: (纸本)9783540255475

Welcome to the proceedings of the 5th international Conference on Scale-Space and PDE Methods in Computer Vision. the scale-space concept was introduced by Iijima more than 40 years ago and became popular later on through the works of Witkin and Koenderink. It is at the junction of three major schools of thought in image processing and computer vision: the design of ?lters, axiomatic approaches based on partial di?erential equations (PDEs), and variational methods for image regularization. Scale-space ideas belong to the mathematically best-understood approaches in image analysis. they have entered numerous successful applications in medical imaging and a number of other ?elds where they often give results of very high quality. this conference followed biennial meetings held in Utrecht, Corfu, Vancouver and Skye. It took place in a little castle (Schl¨ osschen Sch¨ onburg) near the small town of Hofgeismar, Germany. Inspired by the very successful previous meeting at Skye, we kept the style of gathering people in a slightly remote and scenic place in order to encourage many fruitful discussions during the day and in the evening. Wereceived79fullpapersubmissionsofahighstandardthatischaracteristic for the scale-space conferences. Each paper was reviewed by three experts from the Program Committee, sometimes helped by additional reviewers. Based on theresultsofthesereviews,***24manuscripts for oral presentation and 29 for poster presentation.

关键词： image processing and Computer Vision Computer Graphics pattern recognition Artificial Intelligence Numeric Computing

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