2-D Gabor filter based transition region extraction and morphological operation for image segmentation

Abstract

Transition region-based image segmentation techniques have proved effective due to their simplicity and efficient computation. These techniques greatly depend on the accurate extraction of transition regions. Transition region extraction becomes difficult when there is grey level overlapping between foreground and background. Further, the performance of these methods deteriorates when the background and foreground are textured or are of varying intensities. Also, these are applied mostly for single object segmentation. To overcome these shortcomings, we propose a robust hybrid method for image segmentation containing single and multiple objects. The proposed method uses a two-dimensional Gabor filter which enhances the boundaries of object regions for better extraction of transition regions. These transition regions undergo morphological operations to get the object contours and object regions. Finally, objects are extracted from the object regions. Experimental results show that the proposed method yield superior performance for image segmentation containing single and multiple objects.