CONTENT BASED IMAGE RETRIEVAL USING MULTI SVM AND COLOR AND TEXTURE COMBINATION
Journal: International Journal of Engineering Sciences & Research Technology (IJESRT) (Vol.8, No. 3)Publication Date: 3019-03-30
Authors : Navdeep Kaur Jasdeep Singh Mann;
Page : 79-86
Keywords : CBIR; SVM; Content Based Image Retrieval; Modified SVM; Clustering based SVM Technique.;
Abstract
The dramatic rise in the sizes of images databases has stirred the development of effective and efficient retrieval systems. The development of these systems started with retrieving images using textual connotations but later introduced image retrieval based on content. This came to be known as Content Based Image Retrieval or CBIR. Systems using CBIR retrieve images based on visual features such as texture, color and shape, as opposed to depending on image descriptions or textual indexing. In the proposed work we will use various types of image features like color, texture, shape, energy, amplitude and cluster distance to classify the images according to the query image. We will use multi-SVM technique along with clustering technique to compare the features of the input image with the input dataset of images to extract the similar images as that of the query image
Other Latest Articles
- MUTUAL-BENEFIT APPROACH FOR ENERGY-EFFICIENT SEAMLESS MOBILE APPLICATION EXECUTION
- PERFORMANCE AND COMPARATIVE ANALYSIS OF INDIAN STOCK MARKET DATA USING MULTI LAYER FEED FORWARD NEURAL NETWORK AND FUZZY TIME SERIES MULTI LAYER FEED FORWARD NEURAL NETWORK MODEL WITH TRACKING SIGNAL APPROACH
- INDUSTRIAL GEAR TRANSMISSION ERROR MINIMIZATION OPTIMIZATION GA ALGORITHM
- THE ART OF BAGH PRINT TRADITIONAL AND ECO FRIENDLYASPECTS
- EXPERIMENTAL ANALYSIS OF MECHANICAL RESISTANCE IN CONCRETE STRUCTURES WITH FORMATION OF COLD JOINTS INCORPORATED WITH STEEL FIBERS
Last modified: 2019-03-21 07:27:50