Title :
Edge type-selectable active contour using local regional information on extendable search lines
Author :
Phumeechanya, S. ; Pluempitiwiriyawej, C. ; Thongvigitmanee, S.
Author_Institution :
Dept. of Electr. Eng., Chulalongkorn Univ., Bangkok, Thailand
Abstract :
In this paper, we propose a novel active contour method that selects the desirable object based on its edge type. Our method is an extension of the local regional active contour with extendable search lines (LRES). However, we have added to it an ability to look for a particular edge type. To search for the object boundary, the method uses the intensity profile along search lines that are normal to the contour front. The length of these search lines is gradually extended until the object boundary is found. In this paper, we utilize the sign of the difference between the intensity profiles along the search line that are inside and outside the contour as a switching parameter in order to manage the forces that are to drive the contour toward the object with desirable edge type. With the same initial contour, our novel active contour can move toward different objects in the image by setting the edge type parameter. We compare the performance of our edge type selective LRES method to other existing selectable edge type active contour. The results show that our method provides more desirable segmentation outcomes, particularly on some images where other method may fail. Not only is our method robust to noise and able to reach into a deep concave shape, it also has a large capture range and performs well in selecting the object of desirable edge type within the image with the same initial contour.
Keywords :
edge detection; image segmentation; LRES method; desirable object; desirable segmentation outcomes; edge type parameter; edge type-selectable active contour; extendable search lines; intensity profile; local regional active contour; local regional information; novel active contour method; object boundary; switching parameter; Active contours; Force; Image edge detection; Image segmentation; Noise; Pixel; Search problems; Active contours; image segmentation; local regional information; search line; snakes;
Conference_Titel :
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-7992-4
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2010.5650160