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A Survey: Image segmentation Techniques 4th

4th International Conference on Harmony Search, Soft Computing and Applications (ICHSA)

作者： Phonsa, Gurbakash Manu, K. Mewar Univ Chittaurgarh 312901 Rajasthan India Lovely Profess Univ Jalandhar 144403 Punjab India

ISBN: (纸本)9789811307614;9789811307607

Image segmentation is a core step of image processing. Image segmentation is an image processing technique distinct as in which we divide the image into multiple regions in forms of pixel or break down the image into different objects and regions. The main aim of image segmentation is to represent an image on noise-free form. The main use of image segmentation is to detect the objects, relevant data in digital image and their boundaries. These techniques split the image into small regions in order to analyse them and it is also helpful to distinguish the different types of object in single image. Till date, various image segmentation approaches are suggested by researchers with specific aspects or little diversity and commitment for betterment. Researchers work continuously to optimize techniques and enhancing them in order to make image more recognizable, i.e. more smother and noise free. In this paper, as per our study, different researcher works on image processing approaches like thresholding, neural network, edge base segmentation, region base segmentation, etc. are presented.

关键词： segmentation techniques Edge detection boundary-based segmentation Region-based segmentation

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Red blood cell segmentation by thresholding and Canny detector 9

Red blood cell segmentation by thresholding and Canny detect...

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9th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN) / 8th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH)

作者： Al-Hafiz, Fatimah Al-Megren, Shiroq Kurdi, Heba King Saud Univ Dept Comp Sci Riyadh Saudi Arabia

A computer visualization system that can detect, count and classify cells in bioimages is needed, and the segmentation of cells plays a vital role in this type of system. In the medical field, blood cell testing is among the most important types of clinical examinations. Manual blood cell examination methods using microscopic devices are more time consuming than automatic methods and require radiologists with more technical skills. However, the development of an effective and fully automatic segmentation process for RBCs (red blood cells) remains challenging. This paper proposes an automatic segmentation algorithm for RBCs that automatically computes the threshold image using boundary-based methods after enhancing the local and global details of the output using morphological operations to segment red blood cells in bioimages. The proposed segmentation method exhibited an average accuracy rate of 87.9% in a public human red blood cell dataset. Furthermore, a comparison of this method with gold segmentation and two other methods typically used for this purpose demonstrated that the proposed method was highly robust and outperformed the other methods. (C) 2018 The Authors. Published by Elsevier Ltd.

关键词： Red blood cells boundary-based segmentation Gradient magnitude Canny operator

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Red blood cell segmentation by thresholding and Canny detector

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Procedia Computer Science 2018年 141卷 327-334页

作者： Fatimah Al-Hafiz Shiroq Al-Megren Heba Kurdi Department of Computer Science King Saud University Riyadh Saudi Arabia

关键词： Red blood cells boundary-based segmentation Gradient magnitude Canny operator

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An Image segmentation Algorithm for LED Bracket's Detection

An Image Segmentation Algorithm for LED Bracket's Detection

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2016 IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference(IMCEC 2016)

作者： Xinjia Fang Fupei Wu Zhichao Zeng Jintian Li Department of Mechatronic Engineering Shantou University Shantou

ISBN: (纸本)9781509001668

The surface defect detection of LED bracket is an indispensable step to assure its product *** this paper,an image segmentation algorithm method is proposed for LED bracket ***,the basic principle and process of the proposed method is designed and presented,which combines the use of threshold-based segmentation technique and boundarybased segmentation ***,the segmentation results and efficiencies of three methods,including threshold-based segmentation technique,region growing approach and the proposed method,are compared based on LED bracket' s *** the end,the experiment results based on three mentioned methods show that the proposed segmentation approach has the most favorable segmentation results for LED brackets,and its efficiency is higher than the region growing technique,thus it can better meet the requirements of LED stent surface defect detection.

关键词： segmentation algorithms LED bracket thresholdbased segmentation boundary-based segmentation region-based segmentation

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A multiscale optimization approach for the dynamic contour-based boundary detection issue

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COMPUTERIZED MEDICAL IMAGING AND GRAPHICS 2001年第3期25卷 265-275页

作者： Mignotte, M Meunier, J DIRO Dept Informat & Rech Operat Montreal PQ H3C 3J7 Canada

We present a new multiscale approach for deformable contour optimization. The method relies on a multigrid minimization method and a coarse-to-fine relaxation algorithm. This approach consists in minimizing a cascade of optimization problems of reduced and increasing complexity instead of considering the minimization problem on the full and original configuration space. Contrary to classical multiresolution algorithms, no reduction of image is applied. The family of defined energy functions are derived from the original (full resolution) objective function, ensuring that the same function is handled at each scale and that the energy decreases at each step of the deformable contour minimization process. The efficiency and the speed of this multiscale optimization strategy is demonstrated in the difficult context of the minimization of a region-based contour energy function ensuring the boundary detection of anatomical structures in ultrasound medical imagery. In this context, the proposed multiscale segmentation method is compared to other classical region-based segmentation approaches such as Maximum Likelihood or Markov Random Field-based segmentation techniques. We also extend this multiscale segmentation strategy to active contour models using a classical edge-based likelihood approach. Finally, time and performance analysis of this approach, compared to the (commonly used) dynamic programming-based optimization procedure, is given and allows to attest the accuracy and the speed of the proposed method. (C) 2001 Elsevier Science Ltd. All rights reserved.

关键词： active contour model snake multiscale optimization boundary-based segmentation ultrasound medical images

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