Color Image Segmentation

In this work, a new approach to fully automatic color image segmentation, called JSEG, is presented. First, colors in the image are quantized to several representing classes that can be used to differentiate regions in the image. Then, image pixel colors are replaced by their corresponding color class labels, thus forming a class-map of the image. A criterion for “good” segmentation using this class-map is proposed. Applying the criterion to local windows in the class-map results in the “J-image”, in which high and low values correspond to possible region boundaries and region centers, respectively. A region growing method is then used to segment the image based on the multi-scale J-images. Experiments show that JSEG provides good segmentation results on a variety of images.

• Type: Conference
• Year: 1999
• Where: CVPR
• Authors: Yining Deng, B. S. Manjunath, Hyundoo Shin
• Keywords: Computer Vision, CVPR 1999, K-means Clustering Technique, Segmentation Technique