Image Segmentation Based on Discrete Krawtchouk Moment and Quantum Neural Network

摘要：

A new image segmentation method based on discrete Krawtchouk moments and Quantum neural networks is presented. The Krawtchouk moments in certain local window of each pixel in the image are computed and input to quantum neural network. Quantum neural networks, which use multilevel transfer function, have the inherent fuzzy characteristics. The point accommodates to the connatural uncertainty of fractional image data in image segmentation procession. Experiments confirm that the performance of our proposed methods is more accurate and has less iterative time in comparison with the traditional segmentation methods based on Legendre moments and BP neutral networks.

作者: Zhen LIU Jinming SHI Zhongying BAI

作者单位: Beijing University of Posts and Telecommunications, China National Satellite and Meteorologic Centre of China, China

会议类型: 国际会议

会议名称: 2nd IEEE Conference on Industrial Electronics and Applications(ICIEA 2007)(第二届IEEE工业电子与应用国际会议)

会议地点: 哈尔滨

会议语种:英文

在线出版日期: 2007-05-23（万方平台首次上网日期，不代表论文的发表时间）