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检索条件"任意字段=3rd International Conference on Computer Vision and Image Processing, CVIP 2018"

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Automatic image segmentation algorithm for microscopic images of Liquorice and Rhubarb 16

Automatic image segmentation algorithm for microscopic image...

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3rd international Symposium on computer vision and the Internet, visionNet 2016

作者： Vyas, Shraddha Fataniya, Bhupendra Zaveri, Tanish Acharya, Sanjeev Computer Engineering Department Narnarayan Shastri Institute of Technology Jetalpur Ahmedabad India Electronics and Communication Department Nirma University Ahmedabad India Pharmacy Department Nirma University Ahmedabad India

ISBN: (纸本)9781450343015

This paper proposes an automated algorithm for plant identification using microscopic images of powder of herbal plants. In current scenario, the task of identifying plant from its powder form is done by pharmaceutical companies, which perform this task manually. This process takes lots of effort and time. Microscopic image of powder contains varieties of information, which are important evidence for identification of the plant. With every image, different type of noise are present, which makes the segmentation as a critical job. In this paper, we are proposing an algorithm which performs this task automatically by a computer. Our method consists two steps: "Pre-processing" and "image Segmentation". Firstly, microscopic images of "Liquorice" and "Rhubarb" plants were taken. On those images Top-hat and Bot-hat transformation are performed. Wiener Filter is used for image smoothing. An image segmentation is performed using Otsu's thresholding algorithm and find region of interest. The extra blobs were removed using morphological operations. Our proposed algorithm shows the efficiency for successfully detection of Liquorice and Rhubarb plants are 91.37% and 92.94% respectively. © 2016 ACM.

关键词： image segmentation

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Detection and extraction of pantograph region from bank cheque images

Detection and extraction of pantograph region from bank cheq...

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international conference on Signal processing and Integrated Networks (SPIN)

作者： Ashar Ali Rajarshi Pal Indian Institute of Information Technology Allahabad India Institute for Development and Research in Banking Technology Hyderabad India

ISBN: (纸本)9781467391986

image matching and object extraction have been at the heart of computer vision research since the last two decades invigorated by the introduction of SIFT features by David Lowe. This paper proposes an approach for the same for its application to a specific problem, i.e. to extract the rectangular pantograph region from the cheque images used by banks in India. The proposed approach relies upon maximally stable extremal regions (MSER) for the keypoint localization and followed by speeded up robust features (SURF) for feature description. Then, these features from the template are matched with those in the cheque image. After the matching is performed, location of the detected blobs is identified and a binary image is generated with these locations as white and the rest of the background as black. From this binary image, the region of interest can be figured out by simple procedure based on iteration of a rectangular mask sized window throughout the binary image. The location having the largest density of the minority pixels is determined and this region is further extracted out from the initial input image. This is the first attempt of its kind to create an automated technique for extraction of the pantograph region from a cheque image. The results are encouraging. Also, this extraction of the pantograph region can be further applied on other images where it is being used to provide document security.

关键词： Feature extraction Robustness computer vision image edge detection image matching Gray-scale Signal processing

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Novel method for manuscript and inscription text extraction

Novel method for manuscript and inscription text extraction

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international conference on Signal processing and Integrated Networks (SPIN)

作者： N. Jayanthi Prateek Tripathi S. Indu Prashant Gola Electronics and Communication Engineering Department Delhi Technological University Delhi India

ISBN: (纸本)9781467391986

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： Signal processing algorithms image color analysis Clustering algorithms Signal processing Filtering Filtering algorithms Matrix converters

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vision based classification of fresh fruits using fuzzy logic

Vision based classification of fresh fruits using fuzzy logi...

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international conference on Computing for Sustainable Global Development (INDIACom)

作者： Asif Khan Jian-Ping Li Riaz Ahmed Shaikh Imran Khan UESTC School of Computer Science and Engineering Chengdu China BVICAM New Delhi INDIA

ISBN: (纸本)9781467394178

The paper presents a computer vision based system for automatic grading and sorting of agricultural products. The application of machine vision based system, aimed to replace manual based technique for grading and sorting of fruit. The manual examination makes issues in maintaining consistency in grading and sorting. In this research work, a method for sorting and grading of agricultural products like fruits has been proposed. The proposed system starts with catching the fruit's picture utilizing a digital camera. The acquired picture is then processed by using image processing, sorted and grading using methods of fuzzy logic. The classification of fruit is depending upon the object size and shape. Similar shape-size fruit misclassification can reduce by utilizing extra image features, for example, texture and colour. The results obtained are very promising.

关键词： Decision support systems Handheld computers

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Development and Application of the computer vision Technology

Development and Application of the Computer Vision Technolog...

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2016 3rd international conference on Management Innovation and Business Innovation(ICMIBI 2016)

作者： Xiaowen Liu Xinjiang Vocation & Technical College of Construction

The computer vision is the analysis and processing of the visual information by the computer. The theories and technologies related to the researches on the computer vision try to establish a manual system to obtain the information from the images or the multidimensional data. This paper briefly introduces the development of the computer vision, the relationship between the computer vision and the related fields, and the image processing methods in the information processing of the computer vision. The research target of the computer vision is to enable the computers to have the ability of the autonomous adaptation to the environment like the humans through the visual observation and understandings of the world, and to make the computers have the abilities to perceive the geometrical information in the 3D environment including shapes, positions, gestures and motions and so on through the cognition of the two-dimensional images and the three-dimensional environmental information, to carry on the description, storage, identification and understanding.

关键词： computer vision technology Development ideas Application strategy

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A fast texture synthesis using Gene Expression Programming

A fast texture synthesis using Gene Expression Programming

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international conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Jifeng Guo Na Zhang Lin Wang Bo Yang Xiuyang Zhao Jin Zhou Shuangrong Liu Shandong Provincial Key Laboratory of Network based Intelligent Computing University of Jinan Jinan China Information Department China United Network Communications Co. Ltd. Jinan China School of Informatics Linyi University Linyi China

ISBN: (纸本)9781509033683

In computer graphics, vision, and image processing, the texture synthesis occupies an important position. However, most of the existing methods are relatively inefficient. Thus, it is necessary to design a fast texture synthesis algorithm. This article describes an efficient algorithm for texture synthesis. The texture model of this algorithm is derived from the Markov random field. It uses Gene Expression Programming (GEP) to find the best function and the value of each pixel in the synthesized image determined by this function. In this way, this algorithm can avoid scanning all of the pixels, so as to improve the speed of texture synthesis. This algorithm is faster than the previous synthesis algorithm.

关键词： Gene expression Head Algorithm design and analysis Markov processes Programming computer graphics image processing

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Depth-Based Hand Pose Segmentation with Hough Random Forest

Depth-Based Hand Pose Segmentation with Hough Random Forest

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international conference on Green Technology and Sustainable Development (GTSD)

作者： Wei-Jiun Tsai Ju-Chin Chen Kawuu W. Lin Department of Computer Science and Information Engineering National Kaohsiung University of Applied Sciences Kaohsiung Taiwan

ISBN: (纸本)9781509036394

With the development of image processing and computer vision technology, using gesture to communicate with the machine will not only appear in scientific move or just a conceptual product. Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. With this, we can have a more convenient life. Therefore, our goal is using image processing algorithm to effectively recognize the correct gesture from camera and present a user-friendly human-machine interface. In recent years, gesture recognition has become a popular and important issue. It can be used for robot control, appliances control, gaming control, etc. We present an algorithm which is able to correctly calculate the accurate finger joint position and then evaluate the gesture. This algorithm is divided into two parts: hand position detection and gesture recognition. In gesture detection, we capture the depth image from depth camera to solve the problem caused by illumination and background. In gesture recognition, we use an object recognizing algorithm to make the difficult evaluating finger movement problem corresponds to an easier voting classify problem. Depth camera helps our classifier avoid the illumination problem from incorrectly recognizing object.

关键词： Training computer vision Vegetation conferences Pattern recognition Pose estimation Real-time systems

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Detection of Moving Objects Using Foreground Detector and Improved Morphological Filter

Detection of Moving Objects Using Foreground Detector and Im...

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international conference on Information Science and Control Engineering (ICISCE)

作者： Adedeji Olugboja Zenghui Wang Department of Electrical and Mining Engineering University of South Africa Florida South Africa

ISBN: (纸本)9781509025367

The detection of moving object is one of the major steps in computer vision applications such as human-machine interface, medical analysis, robotics, traffic surveillance, etc. In our paper we applied Gaussian Mixture Model (GMM), which is established on background subtraction. Smoothing method was used for the pre-processing stage and morphological filter was applied to remove the unwanted pixels out of the background in other to resolve the background noise disruption problem. We also demonstrated that filtering the foreground segmentation twice with the same morphological structured element but with different width was used to improve the accuracy of the result. Results shows that the proposed method can detect and track effectively the moving cars, compared to filtering the foreground segmentation just once.

关键词： Filtering image segmentation Real-time systems Vehicles computer vision Gaussian mixture model

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Automatic video surveillance for theft detection in ATM machines: An enhanced approach

Automatic video surveillance for theft detection in ATM mach...

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international conference on Computing for Sustainable Global Development (INDIACom)

作者： Rupesh Mandal Nupur Choudhury Computer Science and Engineering Sikkim Manipal Institute of Technology Sikkim INDIA Department of Computer Science Engineering & IT Assam Don Bosco University Guwahati INDIA

ISBN: (纸本)9781467394178

This paper deals with the development of an application for automation of video surveillance in ATM machines and detect any type of potential criminal activities that might be arising with the system which would considerably decrease the inefficiency that are existing in the prevalent systems. An advanced digital image processing technique along with the combination of computer vision and unsupervised machine learning techniques would be utilized which would create phenomenal results in the detection of the activities and their categorization. The proposed system makes efficient utilization of vector graphics and lists out an effective algorithm which comprises of methodologies like background modelling, subtraction, identification of salient objects, tracking of those objects and finally ending up with the detection and identification of the necessary action for the prevention of such type of activities. The proposed system also indulges in semi-supervised learning techniques and uses matching techniques like pose clustering and consistency in order to train the system and develop it to be an automated system as a whole. Since the captured video is fragmented into smaller frames and then the vector graphics and image processing techniques are implemented, the entire mechanism takes place in real time decreasing the time complexity to a great extent making the system an efficient mechanism to prevent such anti-social activities.

关键词： Shape Feature extraction Online banking image edge detection Mathematical model image segmentation Video surveillance

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Particle swarm optimization enabled filtering for fabric images in automated fabric inspection system

Particle swarm optimization enabled filtering for fabric ima...

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international conference on Computing for Sustainable Global Development (INDIACom)

作者： S. Sahaya Tamil Selvi Dept. of Computer Science St. Joseph's College for Women Tirupur India

ISBN: (纸本)9781467394178

Random variations in intensity, poor contrast, variations in illumination are the common reasons for the images to be usually corrupted. These corruptions must be handled by the early stages of vision processing. Even though there are wide varieties of filtering techniques available for the purpose of removing noise in digital images, the problem still remains challenging in research. This paper shows how, Particle Swarm Optimization (PSO) enabled filtering method has been implemented and its performance is compared with the other filtering techniques such as Median, Gaussian filtering methods. The performances of these filtering methods on digital fabric images are assessed based on the metrics Mean squared error (MSE) and Peak signal to noise ratio (PSNR). The implementation results are then compared and evaluated.

关键词： Filtering Fabrics Digital images Inspection conferences Measurement image processing

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