Salient Region Detection based on Object-Biased Gaussian Refinement and Global Contrast

Authors

Cai Qiang, 1. School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China;;2. Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China;
Ziyu Xue, 1. School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China;;2. Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China;
Dianhui Mao, 1. School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China;;2. Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China;
Haisheng Li, 1. School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China;;2. Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China;

Abstract

Abstract: In view of the disadvantages such as the incomplete detection in image boundary which is caused by the global contrast significance detection algorithm, a visual saliency detection algorithm was proposed named salient region detection based on object-biased Gaussian refinement and global contrast. After segmentation based on graph, the global contrast was used to calculate the saliency value of each segmentation blocks. According to the location of the salient object, the center of the Gaussian model was adjusted. Both saliency detection value and Gaussian model combined effect of the final saliency values. The method paid attention to the global contrast and the spatial position of a salient object and improving the way to determine the image center. Theoretical analysis and experiments demonstrate that the method has a better saliency result which can detect the salient object region of all kinds of image effectively. The subjective quality is improved obviously, and the objective indicators are improved partly.

Recommended Citation

Qiang, Cai; Xue, Ziyu; Mao, Dianhui; and Li, Haisheng (2020) "Salient Region Detection based on Object-Biased Gaussian Refinement and Global Contrast," Journal of System Simulation: Vol. 27: Iss. 10, Article 39.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss10/39

First Page

2489

Revised Date

2015-07-24

DOI Link

https://doi.org/

Last Page

2496

CLC

TP391.4

Recommended Citation

Cai Qiang, Xue Ziyu, Mao Dianhui, Li Haisheng. Salient Region Detection based on Object-Biased Gaussian Refinement and Global Contrast[J]. Journal of System Simulation, 2015, 27(10): 2489-2496.