A Study of Low Level Feature Extraction Techniques for Content based Image Retrieval Systems

Abstract: With the development in the computer technologies and the advent of the internet, there has been bang in the amount and the difficulty of digital data being produced, stored, conveyed, analysed, and accessed. The emergence of multimedia technology and the rapidly expanding image collections on the Internet have attracted significant research efforts in providing tools for effective retrieval and management of visual data. Content-based image retrieval (CBIR) is a technique for retrieving images on the basis of automatically-derived features such as colour, texture and shape. Feature extraction is the most important step in image classification. It helps in extracting the feature of an image as ideal as possible. These methods used for content based image retrieval are classified as low-level feature extraction and High-level feature extraction. Low-level feature extractions are based on finding the points, lines, edge, etc. while high level feature extraction methods use the low level feature to provide more significant information for further processing of Image analysis.This paper discusses some of the techniques available for effective extraction of feature for CBIR systems.

Keywords: Content Based Image Retrieval (CBIR), Query by image content (QBIC), Content-based visual information retrieval (CBVIR), Feature Extraction, Low Level Feature extraction.