Content Based Image Retrieval using Combination of Wavelet Transform and Color Histogram

As collections of images are increasing at a rapid rate, demand for effective tools for retrieval of query images from large image databases has increased in significant manner. Among them, content-based image retrieval systems (CBIR) are very popular as they require relatively less human involvement. Contentbased image retrieval (CBIR) mainly deals with the retrieval of most similar images corresponding to a query image from an image database by using its visual contents. It mainly requires feature extraction and computation of similarity. In this paper, we have proposed a content-based image retrieval method that uses a combination of wavelet transform and color histogram. The Haar wavelet transform is used for texture feature extraction, and for color feature extraction we use color histograms. Distance between the query image features and the database images features are computed using Euclidean distance. The proposed system has demonstrated a promising and faster retrieval method on a dataset used for calculation of experimental results. The performance evaluated gives better result as in comparison to the existing systems.

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