Multi Feature Content Based Image Retrieval

There are numbers of methods prevailing for Image Mining Techniques. This Paper includes the features of four techniques I,e Color Histogram, Color moment, Texture, and Edge Histogram Descriptor. The nature of the Image is basically based on the Human Perception of the Image. The Machine interpretation of the Image is based on the Contours and surfaces of the Images. The study of the Image Mining is a very challenging task because it involves the Pattern Recognition which is a very important tool for the Machine Vision system. A combination of four feature extraction methods namely color Histogram, Color Moment, texture, and Edge Histogram Descriptor. There is a provision to add new features in future for better retrieval efficiency. In this paper the combination of the four techniques are used and the Euclidian distances are calculated of the every features are added and the averages are made .The user interface is provided by the Mat lab. The image properties analyzed in this work are by using computer vision and image processing algorithms. For color the histogram of images are computed, for texture co occurrence matrix based entropy, energy, etc, are calculated and for edge density it is Edge Histogram Descriptor (EHD) that is found. For retrieval of images, the averages of the four techniques are made and the resultant Image is retrieved. Keywords-component; Content Based Image Retrieval (CBIR), Edge Histogram Descriptor (EHD),Color moment ,textures, Color Histogram.