Watershed segmentation with boundary curvature ratio based merging criterion

This paper proposes to incorporate boundary curvature ratio, region homogeneity and boundary smoothness into a single new merging criterion to improve the oversegmentation of marker-controlled watershed segmentation algorithm. The result is a more refined segmentation result with smooth boundaries and regular shapes. To pursue a final segmentation result with higher inter-variance and lower intra-variance, an optimal number of segments could be self-determined by a proposed formula. Experimental results are presented to demonstrate the merits of this method.postprintThe 9th IASTED International Conference on Signal and Image Processing (SIP 2007), Honolulu, HI., 20-22 August 2007. In Proceedings of SIP, 2007, p. 7-1

OBJECT-BASED IMAGE ENHANCEMENT TECHNIQUE FOR GRAY SCALE IMAGES

ABSTRACT Image enhancement technique plays vital role in improving the quality of the image. Enhancement technique basically enhances the foreground information and retains the background and improve the overall contrast of an image. In some case the background of an image hides the structural information of an image. This paper proposes an algorithm which enhances the foreground image and the background part separately and stretch the contrast of an image at inter-object level and intra-object level and then combines it to an enhanced image. The results are compared with various classical methods using image quality measures. KEYWORDS Image Enhancement, Morphological watershed segmentation, Object-based contrast enhancement, Interobject stretching, Intra-object stretching

Corner detector based on global and local curvature properties

This paper proposes a curvature-based corner detector that detects both fine and coarse features accurately at low computational cost. First, it extracts contours from a Canny edge map. Second, it computes the absolute value of curvature of each point on a contour at a low scale and regards local maxima of absolute curvature as initial corner candidates. Third, it uses an adaptive curvature threshold to remove round corners from the initial list. Finally, false corners due to quantization noise and trivial details are eliminated by evaluating the angles of corner candidates in a dynamic region of support. The proposed detector was compared with popular corner detectors on planar curves and gray-level images, respectively, in a subjective manner as well as with a feature correspondence test. Results reveal that the proposed detector performs extremely well in both fields. © 2008 Society of Photo-Optical Instrumentation Engineers.published_or_final_versio

WATERSHED SEGMENTATION WITH BOUNDARY CURVATURE RATIO BASED MERGING CRITERION

This paper proposes to incorporate boundary curvature ratio, region homogeneity and boundary smoothness into a single new merging criterion to improve the oversegmentation of marker-controlled watershed segmentation algorithm. The result is a more refined segmentation result with smooth boundaries and regular shapes. To pursue a final segmentation result with higher inter-variance and lower intra-variance, an optimal number of segments could be self-determined by a proposed formula. Experimental results are presented to demonstrate the merits of this method. KEY WORDS Watershed segmentation; merging criterion; boundary smoothness; optimal number of segments 1