Medical Image Retrieval Based on Semantic of Neighborhood Color Moment Histogram
Content-based medical image retrieval is getting more and more importance in aspect of clinical assistant diagnose. This paper in allusion to gastroscopic images, make use of latent semantic indexing technology to implement image retrieval which based on its semantic information. First extract images histogram of neighborhood color moments of low-level features, and then use normalizing, term weighting and singular value decomposition to realize low-level features mapping into high-level semantic features. In this way, the retrieval results will be more in accordance with the doctors comprehension of the images semantic content. The experimental results according to the prototype system show that the approach proposed in the paper could improve the retrieval performance steadily.
histogram of neighborhood color moments latent semantic indezing singular value decomposition gastroscopic image
Qin Chen Xiaoying Tai Yihong Dong Shanliang Pan Xiaoquan Wang Caoqian Yin
Institute of Information Science & Engineering Ningbo University Ningbo, China
国际会议
上海
英文
2221-2224
2008-05-16（万方平台首次上网日期，不代表论文的发表时间）