The goal in image analysis is to extract information useful for solving application based problems. After the image being analyzed, the next step is feature extraction. The primary function of this step is segmentation and transformation [8]. The Image segmentation provides the object features and image transformation provides features based on spatial frequency information.
After this function is performed, the image is modified from lowest level of pixel data to higher level representation [1]. The object features of interest include the geometric properties of binary objects, histogram features and color features. When input data is given to a processor, the data which is fed will be consisting of redundant information [6]. The data should be converted into reduced set of features. This conversion of redundant data into features is called as Feature Extraction [5].
Feature extraction is a part of the data reduction process and is followed by feature analysis. The main aspect of feature analysis is to determine exactly which features are important [3]. So before doing appropriate feature analysis, the concept of Bit-Plane slicing is done. Once the features are extracted, and categorized according to the bit planes the next step is classification.