The image mining technique deals with the extraction of implicit knowledge and image with data relationship or other patterns not explicitly stored in the images. It is an extension of data mining to image domain. The main objective of this paper is to apply image mining in the domain such as breast mammograms to classify and detect the cancerous tissue. Mammogram image can be classified into normal, benign and malignant class. Total of 24 features including histogram intensity features and GLCM features are extracted from mammogram images. A hybrid approach of feature selection is proposed which approximately reduces 75% of the features and new decision tree is used for classification. Experiments have been taken for a data set of 300 images taken from MIAS of different types with the aim of improving the accuracy by generating minimum no. of rules to cover more patterns.
Mohanty, Aswini Kumar and Lenka, Saroj Kumar
"Efficient Image Mining Technique for Classification of Mammograms to Detect Breast Cancer,"
International Journal of Computer and Communication Technology: Vol. 3:
1, Article 9.
Available at: https://www.interscience.in/ijcct/vol3/iss1/9