Research Article
Improving Salient Object via Global Contrast Combined with Color Distribution
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@INPROCEEDINGS{10.1007/978-3-319-46909-6_31, author={Nguyen Duy Dat and Nguyen Thanh Binh}, title={Improving Salient Object via Global Contrast Combined with Color Distribution}, proceedings={Nature of Computation and Communication. Second International Conference, ICTCC 2016, Rach Gia, Vietnam, March 17-18, 2016, Revised Selected Papers}, proceedings_a={ICTCC}, year={2017}, month={1}, keywords={Global contrast Hard threshold Saliency map Derivative operator Color distribution}, doi={10.1007/978-3-319-46909-6_31} }- Nguyen Duy Dat
Nguyen Thanh Binh
Year: 2017
Improving Salient Object via Global Contrast Combined with Color Distribution
ICTCC
Springer
DOI: 10.1007/978-3-319-46909-6_31
Abstract
Salient object detection has many applications for computer vision field. In this paper, we have proposed a method for improving salient object detection which is a combination of global contrast and color distribution. The proposed method has three main steps: to reduce color space, to create salient map and to increase the object quality. The main problems of previous research consist of the consumption of time and the quality of salient map. The proposed method solves two above problems. We used a large dataset to test the proposed method. The proposed method’s result is better than other methods in two points: the running time and the quality of salient map.
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