Segmentation and Location of Abnormality in Cancer Images Using Distributed Estimation

Abstract

 Image segmentation is a technique which divides the image into different features of region and extracts out the interested target. To illustrate the level of the image segmentation in image processing, "image engineering“concept has been introduced which brings the involved theory, methods, algorithms, tools, equipment of image segmentation into an overall framework. With the improvement of computer processing capabilities and the increased application of color image, the image segmentation have become more tedious. This article proposes an image segmentation technique based on clustering algorithm. Image segmentation is a key step in the image processing and image analysis. It needs to extract and separate the features in order to identify and analyze an object. This new architecture includes a hierarchical memory structure to store the cluster centroids for distance calculations and binarytree traversal are employed to compute the nearest centroid operations in pipeline. The advent of reconfigurable logic hardware in the form of Field-Programmable Gate Arrays (FPGAs) allows designs to be quickly developed and prototyped at relatively low cost. The ease of design associated with software and the performance associated with hardware can be achieved using FPGA.

Authors and Affiliations

Amala Silviya. A*

Keywords

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  • EP ID EP122481
  • DOI -
  • Views 79
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How To Cite

Amala Silviya. A* (30).  Segmentation and Location of Abnormality in Cancer Images Using Distributed Estimation. International Journal of Engineering Sciences & Research Technology, 3(4), 7056-7059. https://europub.co.uk/articles/-A-122481