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evocative anatomization through cosaliency technique

R.S.Deepika,J.Divya,D.Mariammal

Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology

ISSN: 2321-3337          Impact Factor:1.521         Volume:4         Issue:3         Year: 05 April,2016         Pages:911-918

International Journal of Advanced Research in Computer Science Engineering and Information Technology

Abstract

Saliency detection approaches a computer vision system for selecting the subset of interesting regions in each input image is processed and analyzed. To detect co-salient images objects professionally, first we use the pre-attentive scheme and then measure the similarity between multiple salient regions to locate the co-salient regions among the group of images. Co-saliency Detection is slightly different technique for simultaneously extracting common salient objects in multiple related images. Conversely, the co-occurring objects detected in image sequences which are visually salient in nature. The Schema of an image processing designed to make the different formats from a copy of the image and to retrieve detailed description about the contents involved. From an existing photograph images, the standard solution will be detecting the noticeable object. Complete experiments of the proposed method over varied publicly available benchmark data sets reveal consistent performance gains over the state-of-the art cosaliency detection methods. The focus of interest detected such as co-occurring objects can benefit the tedious manual labeling process in image frames routinely. In addition, sparse coding is worn for dictionary learning and to update that pre-attentive patch set in co-salient objects.

Kewords

Saliency detection, co-salient images, pre-attentive scheme.

Reference

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