Indian Journal of Science and Technology
Year: 2015, Volume: 8, Issue: 15, Pages: 1-5
Original Article
B. Mohd Jabarullah1*, C. Nelson Kennedy Babu2
1Computer Applications, DTTE, New Delhi - 110068, India
2Thamarabharani Engineering College, Tirunelveli – 627358, Tamil Nadu, India
*Corresponding author
Email: [email protected]
Received Date:02 February 2015, Accepted Date:21 July 2015, Published Date:25 July 2015
The accuracy of face image classification/recognition is absolutely based on the extraction of object of interest in the image. This can be achieved by identifying salient object and eliminating background and other unwanted details. Therefore, this paper proposes a method for object identification and segmentation, which is based on finding fused saliency maps by combining pixel-intensities, visual attracted location of the image and color in the CIEL*a*b* color space. This method uses quadrants and cluster center window of the image without transforming other domain like frequency domain, to obtain saliency maps, in order to minimize time, cost. The object of interest from the original image is segmented using spatial color mapping technique to map saliency image with actual input image using threshold. In order to get perfect segmentation, the input image is subjected to filter and enhanced. This method is effectively applied on data sources such as MSRA, IMM database, and random samplings. The obtained saliency map, subject to binarised, is compared with ground truth using statistical measures such as accuracy, precision and recall, and compared with other methods. As results of this comparison, the proposed method outperforms.
Keywords: Filter, Quadrants Images, Saliency Map, Segmentation, Spatial Color, Threshold
© 2015 Jabarullah and Babu. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)
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