Quick interactive image search in huge databases using Content-Based image retrieval

The number of digital images over the Web is growing by each passing day, indexing this image data based on text is tiresome and error prone. Content-Based image retrieval uses the computer vision techniques to efficiently solve the image retrieval problem. In this research paper we propose a CBIR system which extracts the features of digital image to retrieve similar images from huge databases. We have used Color Histogram, Color Auto-Correlogram, Color Moment, Gabor Wavelet and Discrete Wavelet transform to extract image features. The images are classified using Support Vector Machine (SVM) classifier which effectively distinguishes between relevant and irrelevant images. The results depict that proposed method has better precision and recall rate compared to other methods. The proposed method has average normal precision rate of 0.76 and average normal recall rate of 0.69.