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4th International conference on Geo-Informatics in Resource Management and Sustainable Ecosystem, GRMSE 2016

作者： Wang, Ying Zheng, Kaihui Yu, Mei Du, Baozhen Jiang, Gangyi Faculty of Information Science and Engineering Ningbo University Ningbo315211 China National Key Lab of Software New Technology Nanjing University Nanjing210093 China

ISBN: (纸本)9789811039652

visual quality assessment of stereo image plays an important role in three dimensional visual communication. Considering the processing of binocular perception in viewing stereo image, we present a reduced-reference (RR) stereo image quality assessment (SIQA) model based on binocular perceptual characteristics. Firstly, stereo images are divided into binocular fusion portion and binocular rivalry portion with internal generative mechanism. Then, cyclopean view is generated according to the binocular fusion portion and binocular rivalry portion with binocular perception, and the Gaussian scale mixture RR features from cyclopean view and the binocular rivalry portion for SIQA. Finally, the quality indicators of cyclopean view and binocular rivalry portion are computed to obtain the final SIQA score. The proposed model is tested on the LIVE 3D IQA database. Experimental results show that compared with the state-of-the-art methods, the proposed model has high correlation with subjective perception and can evaluate human stereo visual properties effectively. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Binoculars

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A proposed computer-aided diagnosis system for Parkinson's disease classification using 123I-FP-CIT imaging 3

A proposed computer-aided diagnosis system for Parkinson's d...

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3rd International conference on Advanced Technologies for Signal and image processing, ATSIP 2017

作者： Brahim, Abdelbasset Khedher, Laila Gorriz, Juan Manuel Ramirez, Javier Toumi, Hechmi Lespessailles, Eric Jennane, Rachid Hassouni, Mohammed El Dept. of Signal Theory Networking and Communications University of Granada Spain New Hospital of Orléans Rheumatology Department Orléans45032 France University of Orléans I3MTO Laboratory EA 4708 Orléans45067 France LRIT URAC 29 Faculty of Sciences Mohammed v University in Rabat Morocco

ISBN: (纸本)9781538605516

This paper presents a fully automatic computer aided diagnosis (CAD) system for the classification of Parkinson's disease (PD) by means of functional imaging, such as, the single photon emission computed tomography (SPECT). Firstly, in the preprocessing step, Histogram Equalization (HE) is applied on all the 3D SPECT image data. Secondly, HE is applied on the so-called non-specific (NS) region, as reference region. Then, the normalized images are modelled using Principal Component Analysis (PCA). Thus, for each subject, its scan is represented by a few components. These resulting features will be used for the classification task. The proposed system has been tested on a 269 image database from the Parkinson Progression Markers Initiative (PPMI). Classification rate of 92.63% is achieved, which has proved the robustness and the productiveness of the proposed CAD system in PD pattern detection. In addition, the PCA based feature extraction approach significantly improves the baseline Voxels-as-Features (VAF) method, used as an approximation of the visual analysis. Finally, the proposed aided diagnosis system outperforms several other recently developed PD CAD systems. © 2017 IEEE.

关键词： Principal component analysis

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A novel underwater de-scattering method based on sparse non-negative matrix factorization 3rd

A novel underwater de-scattering method based on sparse non-...

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2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017

作者： Liu, Xiaopeng Saeeda, Hina Dong, Junyu Department of Computer Science and Technology Ocean University of China Qingdao266100 China

ISBN: (纸本)9781538604342

Underwater image processing is a challenging problem due to the scattering effect in the ocean. Floating particles and light attenuation cause underwater images to appear as bluish and blurred. According to the underwater light propagation model, the underwater image can be divided into the direct component and scattering components. In this paper, we propose the Sparse Non-negative Matrix Factorization(SNMF) to remove the scattering effect of the degraded underwater image, which separates the direct light from the scattering light. Through SNMF, the input underwater image can be divided into two additive parts, direct component and scattering component. While the scattering component is constrained to have a relatively low sparseness to obtain the restored underwater image. The experimental results demonstrate that the proposed method has a improved visual quality and equivalent to the state-of-The-Art underwater image processing methods. Moreover it is simple and easy to implement. © 2017 IEEE.

关键词： processing

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Improvement on Tracking Based on Motion Model and Model Updater 2nd

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2nd CCF Chinese conference on Computer Vision (CCCV)

作者： Liu, Tong Xu, Chao Meng, Zhaopeng Xue, Wanli Li, Chao Tianjin Univ Sch Comp Software Tianjin 300354 Peoples R China Tianjin Univ Sch Comp Sci & Technol Tianjin Peoples R China Tianjin Normal Univ Coll Comp & Informat Engn Tianjin Peoples R China

ISBN: (纸本)9789811073052;9789811073045

Motion model and model updater are two important components for online visual tracking. On the one hand, an effective motion model needs to strike the right balance between target processing, to account for the target appearance and scene analysis, to describe stable background information. Most conventional trackers focus on one aspect out of the two and hence are not able to achieve the correct balance. On the other hand, the admirable model update needs to consider both the tracking speed and the model drift. Most tracking models are updated on every frame or fixed frames, so it cannot achieve the best state. In this paper, we approach the motion model problem by collaboratively using salient region detection and image segmentation. Particularly, the two methods are for different purposes. In the absence of prior knowledge, the former considers image attributes like color, gradient, edges and boundaries then forms a robust object;the latter aggregates individual pixels into meaningful atomic regions by using the prior knowledge of target and background in the video sequence. Taking advantage of their complementary roles, we construct a more reasonable confidence map. For model update problems, we dynamically update the model by analyzing scene with image similarity, which not only reduces the update frequency of the model but also suppresses the model drift. Finally, we integrate the two components into the pipeline of traditional tracker CT, and experiments demonstrate the effectiveness and robustness of the proposed components.

关键词： visual tracking Motion model Model updater Saliency detection image similarity image segmentation

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1st International conference on Recent Trends in image processing and Pattern Recognition, RTIP2R 2016

1st International Conference on Recent Trends in Image Proce...

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1st International conference on Recent Trends in image processing and Pattern Recognition, RTIP2R 2016

ISBN: (纸本)9789811048586

The proceedings contain 39 papers. The special focus in this conference is on Recent Trends in image processing and Pattern Recognition. The topics include: Word-level thirteen official Indic languages database for script identification in multi-script documents;skew detection and correction of devanagari script using interval halving method;Eigen value based features for offline handwritten signature verification using neural network approach;an approach for logo detection and retrieval in documents;spotting symbol over graphical documents via sparsity in visual vocabulary;word retrieval from Kannada document images using hog and morphological features;hand drawn symbol recognition in immersive virtual reality using deep extreme learning machines;comparative study of handwritten Marathi characters recognition based on KNN and SVM classifier;recognition of handwritten devanagari numerals by graph representation and lipschitz embedding;combination of feature selection methods for the effective classification of microarray gene expression data;pattern recognition based on hierarchical description of decision rules using choquet integral;classification of summarized sensor data using sampling and clustering: a performance analysis;feature reduced weighted fuzzy binarization for histogram comparison of promoter sequences;a fast k-nearest neighbor classifier using unsupervised clustering;DSS for prognostication of academic intervention by applying DM technique;cluster based symbolic representation for skewed text categorization;performance analysis of impulse noise attenuation techniques;industrial applications of colour texture classification based on anisotropic diffusion and a comprehensive method for assessing the blepharospasm cases severity.

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Detection and Recognition of Flower image Based on SSD network in Video Stream

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Journal of Physics: conference Series 2019年第3期1237卷

作者： Mengxiao Tian Hong Chen Qing Wang China Agricultural University 100083 No. 17 Qinghua East Road China

At present, most flower images could only be recognized but not detected. They can only be used in the scenes with a single target instead of the scenes with two or more targets. Some application scenarios require the human-computer interaction mode with the current location information of flowers; moreover, due to the complexity of the environment and the similarity and difference between flowers, the traditional computer visual methods are inefficient and inaccurate. Therefore, this study introduced SSD deep learning technology into the field of flower detection and identification. The flower data set published by Oxford University was used as the research object, and it was used as the input of the neural network model for training and testing. The experimental results show that the average accuracy is 83.64% based on the evaluation standard of Pascal VOC2007, and 87.4% based on the evaluation standard of Pascal VOC2012. The processing time of an image on PC is 0.13s, which indicates that high-quality automatic detection and recognition can be performed, which can facilitate the retrieval of agricultural plant information database and help people to popularize related information of flowers.

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Design of the control circuit of automatic dryer

Design of the control circuit of automatic dryer

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2nd International conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)

作者： Biqing Li Zhao Li Hongyan Zhang School of Information and Communication Engineering Hezhou University Management Engineering Department Guangxi Vocational and Technical College of Communications

the temperature and humidity of the received signal after processing is sent to the display shows the number, when the value reaches the initial settings required the relay to control the motor, closed, the dryer to stop working, the GSM module and the remote user information exchange, automatically send text messages that have been drying clothes. The design of remote control system to overcome the distance to and understanding the working state and the password protection dryer faults, scalability and use value has a good.

关键词： GSM STC89C52 DHT11 A clothes dryer

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6th International image processing and communications conference, IPandC 2014

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6th International image processing and communications conference, IPandC 2014

ISBN: (纸本)9783319106618

The proceedings contain 39 papers. The special focus in this conference is on image processing and communications. The topics include: Two-Dimensional hidden Markov models in road signs recognition;evaluating the mutual position of objects on the visual scene using morphological processing and reasoning;clustering-based retrieval of similar outfits based on clothes visual characteristics;improving shape retrieval and classification rates through low-dimensional features fusion;accelerating the 3D random walker image segmentation algorithm by image graph reduction and GPU computing;computed tomography images denoising with Markov random field model parametrized by Prewitt mask;Gaussian mixture model based non-local means technique for mixed noise suppression in color images;robust image retrieval based on mixture modeling of weighted Spatio-color information;noise reduction in ultrasound images based on the concept of local neighbourhood exploration;Viterbi algorithm for noise line following robots;hybrid shape descriptors for an improved weld defect retrieval in radiographic testing;on the usefulness of combined metrics for 3D image quality assessment;image processing with process migration;comparison of assessment regularity methods dedicated to isotropic cells structures analysis;a texture-based energy for active contour image segmentation;object localization and detection using variance filter;the impact of the image feature detector and descriptor choice on visual SLAM accuracy and shape versus texture.

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A Novel Vehicle Tracking Algorithm Based on Mean Shift and Active Contour Model in Complex Environment 2

A Novel Vehicle Tracking Algorithm Based on Mean Shift and A...

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conference on Automated visual Inspection and Machine Vision II

作者： Cai, Lei Wang, Lin Li, Bo Zhang, Libao Lv, Wen Minist Commun ITSC Res Inst Highway Key Lab Intelligent Transportat Syst Technol Beijing 100088 Peoples R China Beijing Normal Univ Coll Informat Sci & Technol 19 Xinjiekouwai Rd Beijing 100875 Peoples R China

ISBN: (纸本)9781510611146;9781510611139

Vehicle tracking technology is currently one of the most active research topics in machine vision. It is an important part of intelligent transportation system. However, in theory and technology, it still faces many challenges including real-time and robustness. In video surveillance, the targets need to be detected in real-time and to be calculated accurate position for judging the motives. The contents of video sequence images and the target motion are complex, so the objects can't be expressed by a unified mathematical model. Object-tracking is defined as locating the interest moving target in each frame of a piece of video. The current tracking technology can achieve reliable results in simple environment over the target with easy identified characteristics. However, in more complex environment, it is easy to lose the target because of the mismatch between the target appearance and its dynamic model. Moreover, the target usually has a complex shape, but the tradition target tracking algorithm usually represents the tracking results by simple geometric such as rectangle or circle, so it cannot provide accurate information for the subsequent upper application. This paper combines a traditional object-tracking technology, Mean-Shift algorithm, with a kind of image segmentation algorithm, Active-Contour model, to get the outlines of objects while the tracking process and automatically handle topology changes. Meanwhile, the outline information is used to aid tracking algorithm to improve it.

关键词： Machine vision image processing target recognition object tracking mean shift algorithm active contour model

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A spectral graph based image coding method

A spectral graph based image coding method

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IEEE Signal processing and communications Applications (SIU)

作者： Ali Can Yağan Mehmet Tankut Özgen Elektrik-Elektronik Mühendisliği Bölümü Anadolu Üniversitesi Eskişehir Türkiye

In this paper, a spectral graph based image coding method is proposed. In the proposed method, only the smoothing parameter in the graph adjacency matrix, graph Fourier transform (GFT) coefficients kept after hard thresholding and column indices of eigenvectors corresponding to kept coefficients are sent to the decoder side. It is advantageous in that this coding process is performed by sending much less information as compared to other graph based methods. Our results indicate that our proposed method enables image compression without deteriorating the visual quality by using very small numbers of GFT coefficients.

关键词： image coding Fourier transforms Signal processing image denoising Information processing Transform coding

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