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A Novel approach for Image Segmentation using SOM 1
| Content Provider | Semantic Scholar |
|---|---|
| Author | Valarmathi, P. Aruna, M. |
| Abstract | This paper proposes a novel approach to extract image features like contour extraction and edge detection for image segmentation with self organizing properties for a network of adaptive elements. Segmentation is a collection of methods allowing to interpret parts of the image as objects. The object is everything what is of interest in the image and the rest of the image is background. Through experiments, the proposed approach will be intensively evaluated by applying a large number of segmentation tests to medical images. I. Introduction Image segmentation refers to the process of partitioning a digital image into multiple regions (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. The result of image segmentation is a set of regions that collectively cover the entire image, or a set of contours extracted from the image. Some of the practical applications of image segmentation are [3]: Medical Imaging 1. Locate tumors and other pathologies • Measure tissue volumes • Computer-guided surgery • Diagnosis • Treatment planning • Study of anatomical structure • Locate objects in satellite images (roads, forests, etc.) 2. Face recognition 3. Automatic BLOCKINtraffic BLOCKINcontrolling BLOCKINsystems 4. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.ijcst.com/icaccbie11/sp1/pvalarmathi.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
