A Neural Network Approach to Mammogram Image Classification Using Fractal Features
This paper presents a novel method based on frac-tal features for the classification of mammogram images. For recognition of regions and objects in the natural scenes, there is always a need for features, which are invariant, and they provide a good set of descriptive values for the region. There are numerous methods available to estimate parameters from the images of the fractal surface. In this paper we perform mammogram image classification based on fractal dimension and fractal signature. The result has shown the potential usefulness of the fractal features for image analysis. A trainable multilayer feed forward neural network has been designed for the classification of images. Experimental results shown that the proposed system can well perform a classification rate of 98％.
Fractal Dimension Fractal Signature Mammo-gram invariant- methods data analysis
S.Don Duckwon Chung K.Revathy Eunmi Choi Dugki Min
School of Computer Science and Engineering,Konkuk University,Hwayang-dong,Kwangjin-gu,Seoul,133-701, Department of Computer Science,University of Kerala,Trivandrum,India School of Business IT,Kookmin University,Jeongneung-dong,Seongbuk-gu,Seoul,136-792,Korea
国际会议
上海
英文
2973-2976
2009-11-20（万方平台首次上网日期，不代表论文的发表时间）