Wavelet Analysis: Comparison of Approximation and Details For Mammogram Classification

Image features extraction is an important step in image
processing techniques. The features of digital images can
be extracted directly from the spatial data or from a
different space. Using a different space by special data
transforms such wavelet can be helpful to extract specific
characteristics from a data. Wavelets prove an efficient
representation of image. It decomposes an image into
subbands, approximation, horizontal, vertical and
diagonal. This paper presents an attempt to find which
subband that could be better to used for mammogram
classification to detect and diagnose the breast cancer.