JELE_V2_N1_RP6 E. Suresh Babu S. Salma A. Reshma C. Nagaraju Journal on Electronics Engineering 2249 – 0760 2 1 45 50 ENI, Local Binary Pattern, Rotation Invariance, Classification and Directional Magnitude This paper proposes a new LBP with ENI approach to extract local image features for the purpose of Images classification. This new LBP method introduces the notion of ENI (the abbreviation for “edge pixels, noisy pixels and interior pixels”) which denotes the number of homogeneous pixels in a local neighborhood, and is significantly different for edge pixels, noisy pixels and interior pixels. The authors redefine the controlling speed function and the controlling fidelity function to depend on ENI. According to our controlling function, the diffusion and fidelity process at edge pixels, noisy pixels and interior pixels can be selectively carried out. Further, a class of second-order improved, edge-preserving denoising method is applied based on the controlling function in order to deal with random-valued impulse noise reliably. The experimental results on representative image databases show that the proposed method is robust to noise and can achieve significant improvement in terms of the obtained classification accuracy in comparison to the LBP method and it's extensions. September - November 2011 Copyright © 2011 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=1581