Image Segmentation Via Color Clustering
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2014, Vol 5, Issue 7
Abstract
This paper develops a computationally efficient process for segmentation of color images. The input image is partitioned into a set of output images in accordance to color characteristics of various image regions. The algorithm is based on random sampling of the input image and fuzzy clustering of the training data followed by crisp classification of the input image. The user prescribes the number of randomly selected pixels comprising the trainer set and the number of color classes characterizing the image compartments. The algorithm developed here constitutes an effective preprocessing technique with various applications in machine vision systems. Spectral segmentation of the sensor image can potentially lead to enhanced performance of the object detection, classification, recognition, authentication and tracking modules of the autonomous vision system.
Authors and Affiliations
Kaveh Heidary
Keywords
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- EP ID EP99815
- DOI 10.14569/IJACSA.2014.050702
- Views 104
- Downloads 0
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