Feature Selection and Extraction for Content-Based Image Retrieval

Content-Based Image Retrieval is a technique that utilizes the visual content of an image to search for similar images in large scale image databases. The visual content of an image represents the low-level features extracted from the image. These primarily constitute color, shape and texture features. The precision of image classification and image retrieval is mainly based on image feature extraction. More distinguished image features will yield better results in classification and retrieval process. Thus feature selection and feature extraction are the important tasks to be considered in image retrieval process. This paper aims to discuss about feature selection and an efficient method for feature extraction is proposed for image retrieval process. Keywords— Content-Based Image Retrieval, Euclidean Distance Method, Relevance Feedback, Feature Vector