Content Based Image Retrieval using Color Feature Extraction with KNN Classification
Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.3, No. 5)Publication Date: 2014-05-30
Authors : PRAGATI ASHOK DEOLE; RUSHI LONGADGE;
Page : 1274-1280
Keywords : Image Retrieval; Content based image retrieval; Color Model; KNN Algorithm; Relative Standard Derivation;
Abstract
Image Retrieval system is an effective and efficient tool for managing large image databases. Content based image retrieval system allows the user to present a query image in order to retrieve images stored in the database according to their similarity to the query image. Content Based Image Retrieval (CBIR) is a technique which uses visual features of image such as color, shape, texture, etc. to search user required image from large image database according to user’s requests in the form of a query. In this paper content based image retrieval method is used retrieve query image from large image database using three features such as color, shape, texture etc. The main objective of this paper is classification of image using K-nearest neighbors Algorithm (KNN).
Other Latest Articles
- Partial Purification of Alpha-Amylase Produced by Brevibacillus Borstelensis R1
- Wide-Band Current Starved Ring CMOS Voltage Controlled Oscillator (VCO) using 0.18 μm CMOS Technology
- A Study on Different Feature Level Learning and Prediction Approaches
- Performance Enhancement of Household Refrigerators with Cooling of Compressor: A Review
- Case Study: Exergy and Energy Analysis of Hot Water Loop and Branch Network Using Two CHP
Last modified: 2014-06-04 22:43:37