Title :
Morphological decomposition of arbitrarily shaped images
Author :
Yang, Hsin-Tai ; Lee, Shie-Jue
Author_Institution :
Dept. of Electr. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan
Abstract :
Decomposition of images is a very important issue in pattern analysis and recognition. Especially, for image processing systems that can not handle large size of images, image decomposition is the only way to overcome this difficulty. The technique presented in this paper is based on mathematical morphology and decomposes a binary structuring element into dilations of smaller size of images (factors). Park and Chin (1995) proposed a method of morphological decomposition of simply connected images into 3×3 size factors. We extend their theorem to make it possible for any n×n size factors. A method for optimal decomposition is also discussed. Based on this method, users can therefore select their favorable shape of structuring elements to process images efficiently
Keywords :
codes; image processing; mathematical morphology; set theory; arbitrarily shaped images; binary structuring element; dilations; image decomposition; image processing systems; mathematical morphology; morphological decomposition; optimal decomposition; simply connected images; Concurrent computing; Image decomposition; Image edge detection; Image processing; Image recognition; Morphology; Pattern analysis; Pattern recognition; Pipelines; Shape;
Conference_Titel :
Systems, Man, and Cybernetics, 1996., IEEE International Conference on
Print_ISBN :
0-7803-3280-6
DOI :
10.1109/ICSMC.1996.569841