Wavelet based transition region extraction for image segmentation

Abstract

Transition region based approaches are recent hybrid segmentation techniques well known for its simplicity and effectiveness. Here, the segmentation effectiveness depends on robust extraction of transition regions. So, we have proposed a transition region method which initially decomposes the gray image in wavelet domain. Two existing transition region approaches are applied on approximate coefficients to extract transition region feature matrix. Using this feature matrix the corresponding prominent wavelet coefficients of different bands are found. Inverse wavelet transform are then applied on the modified coefficients to get edge image with more than one pixel width. Otsu thresholding is applied on it to get transition regions. Further, morphological operations are applied to extract the object regions. Finally, the objects are extracted using the object regions. The wavelet domain approach extracts robust transition regions resulting in better segmentation. The proposed method is compared with different existing image segmentation methods. Experimental results reveal that the proposed method achieve 0.95 overall segmentation accuracy. It also works well for extraction of single as well as multiple objects from images.