Rupali Patil
ABSTRACT
The feature extraction-coding-pooling framework improves the performance of image classification because it generates robust and discriminative image representation. The proposed system uses saliency driven multi-scale nonlinear diffusion filtering with linear distance coding (LDC) method for image classification. The saliency driven multi-scale nonlinear diffusion filtering generates the images at small, mid and high scale and concatenation of information at these scales produces robust image classification using LDC. The class manifolds generated by this classification system are given as input to image retrieval system which finally retrieves all images those are relevant to supplied image.
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