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检索条件"任意字段=International Conference on Computer Vision and Image Processing, CVIP 2016"

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Toward device assisted identification of grocery store sections and items for the visually impaired

Toward device assisted identification of grocery store secti...

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2016 international conference on image processing, computer vision, and Pattern Recognition, IPCV 2016

作者： Alhalabi, Wadee Attas, Dalia Department of Computer Science Faculty of Computing and IT King Abdul-Aziz University Jeddah Saudi Arabia

ISBN: (纸本)1601324421

- There are systems developed to assist the visually impaired in grocery shopping. The developed systems require physical work from the users, wireless connections and products database to obtain the products information. Here comes the need for a system that assist the visually impaired person in grocery shopping without any additional devices. The system should use object recognition algorithms instead of wireless connections and database to recognize products. In the paper, a software system was created to solve the problem of assisting the visually impaired in grocery shopping. The created software accomplished only the mission of recognizing the grocery products on shelves. The paper recommends implementing a shopping cart consists of three cameras installed vertically on one side of the cart. We conducted a comparison between two object recognition algorithms to recognize products on the aisle shelves. A multimodal system created to fuse the results of the used object recognition algorithms. © CSREA Press.

关键词： Optical character recognition

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Error reduction of the absolute phase recovered from three sets of fringe patterns with selected wavelengths

Error reduction of the absolute phase recovered from three s...

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2016 international conference on image processing, computer vision, and Pattern Recognition, IPCV 2016

作者： Long, Jiale Xi, Jiangtao Zhang, Jianmin Ding, Yi School of Information Engineering Wuyi University Jiangmen Guangdong China School of Electrical Computer and Telecommunications Engineering University of Wollongong WollongongNSW Australia School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan Hubei China

ISBN: (纸本)1601324421

-In a recent published work we proposed a technique to recover the absolute phase maps of three sets of fringe patterns with selected wavelengths. It is demonstrated that the absolute phase maps can be unwrapped from the wrapped phase maps by the three-step phase-shifting profilometry (PSP), using only 9 fringe patterns. However, few incorrect values still remain in the recovered absolute phase. In this paper, we develop a method to correct and remove the errors in the recovered absolute phase. The experiments validate the effectiveness of our proposed method. © CSREA Press.

关键词： Errors

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A quantitative analysis of tilt in the Cafe Wall illusion: a bioplausible model for foveal and peripheral vision

A quantitative analysis of tilt in the Cafe Wall illusion: a...

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international conference on Digital image Computing - Techniques and Applications (DICTA)

作者： Nematzadeh, Nasim Powers, David M. W. Flinders Univ S Australia Sch Comp Sci Engn & Math Adelaide SA Australia

ISBN: (纸本)9781509028962

The biological characteristics of human visual processing can be investigated through the study of optical illusions and their perception, giving rise to intuitions that may improve computer vision to match human performance. Geometric illusions are a specific subfamily in which orientations and angles are misperceived. This paper reports quantifiable predictions of the degree of tilt for a typical geometric illusion called Cafe Wall, in which the mortar between the tiles seems to tilt or bow. Our study employs a common bioplausible model of retinal processing and we further develop an analytic processing pipeline to quantify and thus predict the specific angle of tilt. We further study the effect of resolution and feature size in order to predict the different perceived tilts in different areas of the fovea and periphery, where resolution varies as the eye saccades to different parts of the image. In the experiments, several different minimal portions of the pattern, modeling monocular and binocular foveal views, are investigated across multiple scales, in order to quantify tilts with confidence intervals and explore the difference between local and global tilt.

关键词： Visual perception Bioinspired neural networks Geometric illusions Cafe Wall illusion Tilt effects Difference of Gaussian Pattern recognition

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Novel Method for Manuscript and Inscription Text Extraction 3

Novel Method for Manuscript and Inscription Text Extraction

引用

3rd international conference on Signal processing and Integrated Networks (SPIN)

作者： Jayanthi, N. Tripathi, Prateek Indu, S. Gola, Prashant Delhi Technol Univ Elect & Commun Engn Dept Delhi India

ISBN: (纸本)9781467391979

computer vision involves image processing which has the use of various algorithms for text extraction as an integral part. This paper delves into the use of filtering based thresholding on HSV plane which serves as a common tool for text extraction in manuscripts as well as inscriptions. The basic and simple technique proposed has provided positive results for various images as compared to the other commonly used complex algorithms. The paper also involves a comparison with various other algorithms which is the nick, niblack, Messalodi, Otsu, Gllavata, Kim, Lee, Color Clustering Technique and FastICA helping us understand the advantages that this algorithm presents.

关键词： Hue Saturation Value Plane image processing Text Extraction manuscripts inscriptions

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APPROACHES OF ARTIFICIAL INTELLIGENCE IN BIOMEDICAL image processing

APPROACHES OF ARTIFICIAL INTELLIGENCE IN BIOMEDICAL IMAGE PR...

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IEEE international conference on Advances in Computing, Communication and Automation (ICACCA)

作者： Shukla, Shruti Lakhmani, Ashish Agarwal, Ambuj Kumar Babu Banarsi Das Northern India Engn Coll Dept Biomed Engn Faizabad Rd Lucknow 226028 Uttar Pradesh India Babu Banarsi Das Natl Inst Technol & Management Dept Comp Sci Engn Faizabad Rd Lucknow 226028 Uttar Pradesh India Teerthankar Mahaveer Univ Coll Comp Sci & Informat Technol Moradabad India

ISBN: (纸本)9781509006731

Artificial Intelligence or AI is a subfield of computer science, which can be defined as the intelligence exhibited by a machine or a software having a remarkable impact on the field of biology and medicine. Imaging, on the other hand has become an essential component of many fields in medicine, biomedical applications, biotechnology and laboratory research by which images are processed and analysed. Putting together AI and imaging, the tools and techniques of artificial intelligence are useful for solving many biomedical problems and using a computer based equipped hardware software application for understanding images, researchers and clinicians can enhance their ability to study, diagnose, monitor, understand and treat medical disorders. Therefore the main idea behind this research paper is to focus on understanding the artificial intelligence, its concepts and various models available for the segmentation(or classification) of medical images, its applications, advantages and disadvantages and results and more.

关键词： Artificial intelligence fuzzy logic medical imaging medical tools neural networks segmentation methods

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computer vision Techniques for Automatic Determination of Yield Effective Bad Condition Storage Effects on Various Agricultural Seed Types 5

Computer Vision Techniques for Automatic Determination of Yi...

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5th international conference on Agro-Geoinformatics (Agro-Geoinformatics)

作者： Aygun, Sercan Gunes, Ece Olcay Istanbul Tech Univ Elect & Elect Engn Fac Dept Elect & Commun Engn Istanbul Turkey

ISBN: (纸本)9781509023509

Plant seeds can be preserved for a long time. Longterm storage of seeds is very important for the continuity of life. Seed storage time heavily depends on plant species, seed maturation degree, preliminary processing, seed germination value and the moisture content. Environmental conditions such as temperature of the storage place, humidity, and light, or infestation of parasitic living beings;insects and fungus are some other first order parameters responsible for the seed storage time, too. Germinated and bug infested seeds are neither suitable for food consumption nor for cultivation. Automated discrimination of these situations with respect to healthy seeds requires an algorithm to be applied in the sense of seed image classification. This paper draws some image processing related steps to be applied for seed images which discriminate the germinated or bug infested ones. The problem itself stems from the seed type, the reason why some seed variations like beans show close texture to germinated sprouts. The experiments are handled by using some sort of seed types readily available in the seedsman such as lentil, chickpea, bean, corn, barley, cowpea, and wheat seeds. Each of the training and test pictures is obtained in an uncontrolled environment without the care of light and image acquisition details that makes the problem tougher. A brand-new database namely ITUSEED-II has already been constructed. The analysis of database related to healthy and badly conditioned seeds using a new computer vision method namely Relational Bit Operator (RBO) is presented in this paper.

关键词： computer vision germination image processing infestation Relational Bit Operator seed classification

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Maximal Margin Feature Mapping via Basic image Descriptors for image Classification

Maximal Margin Feature Mapping via Basic Image Descriptors f...

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IEEE international conference on Industrial Technology (ICET)

作者： Zhao, Changchen Lin, Chun-Liang Chen, Weihai Natl Chung Hsing Univ Dept Elect Engn Taichung 40227 Taiwan Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China

ISBN: (纸本)9781467380751

computer vision is one of the most important branches in modern industrial technology. image classification plays an important role in computer vision since it utilizes the most advance technique in this area. However, most image classification methods only use the SIFT feature for further processing, which hinders the rich useful low-level image attributes to be captured. This paper proposes a maximal margin feature mapping framework that incorporates basic descriptors in the recognition system. This is fulfilled by optimizing an objective function that minimizes intra-class distance and maximizes interclass distance as well as the reconstruction error. An efficient optimization algorithm is proposed to learn the transformation matrix. Experiments on three publicly available datasets are conducted. The preliminary results show the effectiveness of the proposed approach.

关键词： image classification maximal margin feature mapping non-convex optimization

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MRI denoising using randomized version of nonlocal means method

MRI denoising using randomized version of nonlocal means met...

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2016 international conference on image processing, computer vision, and Pattern Recognition, IPCV 2016

作者： Hu, Jinrong He, Jia Fu, Ying Wu, Xi Zhou, Jiliu School of Computer and Soft Engineering Xihua University Chengdu610039 China Key Laboratory of Pattern Recognition and Intelligent Information Processing Chengdu University Chengdu610106 China School of Computer Science Chengdu University of Information Technology Chengdu610225 China

ISBN: (纸本)1601324421

- Non-local mean (NLM) algorithm has been implemented effectively in MRI denoising and is always limited by its computational complexity. To reduce the computational burden of NLM in 3D MRI dataset, in this paper, we used a randomized version of NLM algorithm to remove the noise in MRI data. The random NLM algorithm seeds up the classical NLM by computing a small subset of image patch distances, which are randomly select according to the uniform sampling pattern. Numerical experiments demonstrate that the random NLM can achieve a competitive denoising result at a low sampling rate (0.05) in 3D MRI dataset while reducing the runtime dramatically. © CSREA Press.

关键词： Magnetic resonance imaging

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An improved feature image matching algorithm based on Locality-Sensitive Hashing 13

An improved feature image matching algorithm based on Locali...

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13th IEEE international conference on Signal processing (ICSP)

作者： Wu, Tianjia Miao, Zhenjiang Beijing Jiaotong Univ Inst Informat Sci Beijing Peoples R China

ISBN: (纸本)9781509013456

image matching is a classic technique in computer vision. However, the traditional local invariant features image matching algorithm has two problems, narrow scale range and long time consuming. Aiming at these problems, we proposed a fast image matching algorithm with the aid of improved local invariant features based on Locality-Sensitive Hashing. Firstly, by building simple Gaussian pyramid and achieving FAST keypoint detection, keypoints are extracted from the reference image and the candidate matching image. Then Fast Retina Keypoint feature descriptor is calculated and weighted. Furthermore, the high-dimensional data is mapped to a low dimensional space and hash indexes are built through the local sensitive hashing algorithm in aiming of finding the approximate nearest neighbor. The experimental results in different datasets indicate that the improved algorithm achieves real-time processing in image matching, and has better robustness and shorter processing time than most classical methods.

关键词： Gaussian pyramid FREAK LSH feature matching

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A GPU based implementation of Robust Face Detection System 4

A GPU based implementation of Robust Face Detection System

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4th international conference on Recent Trends in computer Science and Engineering (ICRTCSE)

作者： Jain, Vaibhav Patel, Dinesh DAVV Indore Dept Comp Engn Inst Engn & Technol Indore 452017 Madhya Pradesh India

Face detection is the active research area in the field of computer vision because it is the first step in various applications like face recognition, military intelligence and surveillance, human computer interaction etc. Face detection algorithms are computationally intensive, which makes it is difficult to perform face detection task in real-time. We can overcome the processing limitations of the face detection algorithms by offloading computation to the graphics processing unit (GPU) using NVIDIAs Compute Unified Device Architecture (CUDA). In this paper, we have developed a GPU based implementation of robust face detection based on Viola Jones face detection algorithm. To verify our work, we compared our implementation with traditional CPU implementation for same algorithm. (C) 2016 The Authors. Published by Elsevier B.V.

关键词： Face Detection GPU CUDA Integral image

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