Enhancing Content Based Image Retrieval Technique by Observing Image Feature Extraction Methods

From the last few years, database of digital images has advanced substantially along with the techniques for image processing. Today, the databases of digital image are found in an increasing number, that provide useable and effective access to image collections. Image databases are becoming larger and more prevalent as a result of the Internet’s spread and the accessibility of optical imaging technologies like digital camera systems and scanning of images, necessitating the development of image retrieval methods that are more productive and useful. The research focuses on feature’s selection for extracting them in view to enhance the result of content-based image retrieval system. Identification of image features, corelating them on the basis of their effects, and the influence of these factors on retrieval are all part of this process. Low-level visual features that address more detailed perceptual components of visual data are observed along with high-level features that underpin in image retrieval techniques. As a result, the research is attempting to review these elements for improving the efficiency of CBIR search results. Further, in order to recognize the wider conceptual features of visual data, various features can be integrated with one another.