A Comprehensive Survey of Image Search Based on Visual Similarity

Abstract: Image search based on visual similarity is the widely applicable image processing method, which is used extensively. One of the important stage in content based image retrieval system is Feature Extraction, where low level features are extracted from image, then The features vector is formed by the extracted features. Feature Extraction is used for indexing images and interpretation of image. Effective storage, ranking and organizing a large image database is a critical issue in computer systems. To overcome these problems many methods has proposed. However, the accuracy and speed of image retrieval is still an interesting topic of research. This paper presents a survey of various states-of-the-art- image search techniques such as color edge detection, Discrete Wavelet Transform and Singular value decomposition etc. that allows faster and effective visual similarity search.

Keywords: Feature Extraction, Similarity Matching, Canny Edge Detection, Color Edge Detection, Haar Wavelet Transform, singular value decomposition.