Color Histogram Features for Image Retrieval Systems
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Histogram features have proved powerful in the classification of image and object detection . The CBIR most efficient and searches the color based images. Here in this method we use some improved preprocessing steps, preprocessing algorithms and the image classification is analyzed. In CBIR image classification has to be computationally very fast and efficient. In this project a new approach is introduced, which based on low level image histogram features. Color is a main powerful descriptor that often identifies object and extraction scene. The main advantage of this method is the very quick generation and comparison of the applied feature vectors. Histograms are simple to calculate in software and also lend themselves to economic hardware implementations. A popular tool for a real-time image processing histogram-based image retrieval methods in two color spaces were exhaustively compared. The testing also highlights the weaknesses and strengths of the model.