Research On The Method Of Region-based Color Image Segmentation

Image segmentation is a fundamental and important technology in image project.It is the primary task in any image analysis and image recognition process.With the impro- Ving of the computer processing capability and the increasing of the color image applic- ation,the researchers are paying more attention to the color image segmentation.The methods of the color image segmentation can be seen as the extension of the methods of the gray image segmentation,but many methods of the original gray image segmentation can not be directly applied to the color images.So it requires the combination of color image information-rich features to improve the methods of the original gray image segmentation or develops a method that is devoted to the color image segmentation.This paper introduces a method of region-based color image segmentation. This method first extracts color, texture, and location features for each pixel form integrative feature vectors by selecting suitable color space and the feature space is formed. Then, in this feature space, first of all,the best cluster number and the initial cluster center are obtained by improved ISODATA algorithm and then an image is clustering and is separated into regions by K-means clustering alogorithm.Finally,the features of regions are extracted .The experiment results and the comparision results with the similar approach are provided.In order to analyze performance of the algorithm, we use multiple images to be verified and the results are analyzed. Experiment results show the proposed method has the quickly segmentation speed and good segmentation results.