Image segmentation using intensity and color information

We have developed an advanced segmentation algorithm using color information as well as intensity information. Combining both kinds of information yields robust and better segmentation results in terms of perception. Our segmentation algorithm consists of joint marker extraction, region growing and region merging. We have introduced a new algorithm for extracting markers out of images using both color and intensity information. Morphological open-close by reconstruction filters are applied for intensity based marker extraction. In color based marker extraction, quantized HSV color values are employed. Joint markers are defined as the sum of both kinds of markers. The region growing process is applied after the marker extraction process until all of the uncertain pixels belong to either of the marker regions. Our proposed process is based on a watershed algorithm which is a powerful morphological decision tool. After the region growing process, region merging using color information is employed. This process is applied in order to reduce segmented regions while preserving meaningful information. Finally, our experimental results are shown using "akiyo" and "foreman" sequences.