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The problem of mammographic image classification has been handled using various measures and features. The methods consider only small set of features to perform classification, but still the methods suffer to produce efficient classification accuracy. To overcome the problem of accuracy in mammographic image classification, a region-specific multi-attribute white mass estimation technique is proposed. The method uses the white mass value, density measure, and binding to identify the microcalcification. First, the peak white mass value is identified by visiting throughout the mammogram region. Second, the method splits the mammographic image into a number of small scale integral images. Third, for each integral image, the method computes multi-attribute white mass value, and based on computed white mass value, the method identifies the region being affected by the calcification. The method produces efficient result in mammogram image classification.
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