A visual saliency detection algorithm based on channel selecting in transform domains

2014 ◽  
Author(s):  
Shen Yifeng ◽  
Niu Yifeng ◽  
Shen Lincheng
Keyword(s):  
Saliency Detection ◽  
Visual Saliency ◽  
Detection Algorithm ◽  
Visual Saliency Detection ◽  
Transform Domains

Double Feature Combination: Region Contrast for Visual Salient Object Detection

2012 ◽  
Vol 239-240 ◽  
pp. 811-815
Author(s):  
Zhi Hai Sun ◽  
Teng Song ◽  
Wen Hui Zhou ◽  
Hua Zhang
Keyword(s):  
Object Detection ◽  
Saliency Detection ◽  
Visual Saliency ◽  
Recall Rate ◽  
Detection Algorithm ◽  
Salient Object Detection ◽  
Color Contrast ◽  
Salient Object ◽  
Histograms Of Oriented Gradients ◽  
Visual Saliency Detection

Visual saliency detection has become an important step between computer vision and digital image processing. Recent methods almost form a computational model based on color, which are difficult to overcome the shortcoming with cluttered and textured background. This paper proposes a novel salient object detection algorithm integrating with region color contrast and histograms of oriented gradients (HoG). Extensively experiments show that our algorithm outperforms other state-of-art saliency methods, yielding higher precision and better recall rate, even lower mean absolution error.

scholarly journals The Study of Randomized Visual Saliency Detection Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-9
Author(s):  
Yuantao Chen ◽  
Weihong Xu ◽  
Fangjun Kuang ◽  
Shangbing Gao
Keyword(s):  
Image Segmentation ◽  
Detection Method ◽  
Saliency Detection ◽  
Visual Saliency ◽  
Detection Algorithm ◽  
Saliency Map ◽  
Input Image ◽  
Memory Space ◽  
Segmentation Process ◽  
Visual Saliency Detection

Image segmentation process for high quality visual saliency map is very dependent on the existing visual saliency metrics. It is mostly only get sketchy effect of saliency map, and roughly based visual saliency map will affect the image segmentation results. The paper had presented the randomized visual saliency detection algorithm. The randomized visual saliency detection method can quickly generate the same size as the original input image and detailed results of the saliency map. The randomized saliency detection method can be applied to real-time requirements for image content-based scaling saliency results map. The randomization method for fast randomized video saliency area detection, the algorithm only requires a small amount of memory space can be detected detailed oriented visual saliency map, the presented results are shown that the method of visual saliency map used in image after the segmentation process can be an ideal segmentation results.

Unsupervised visual saliency detection via information content measuring

2012 ◽  
Vol 48 (25) ◽  
pp. 1591-1593 ◽  
Author(s):  
Di Wu ◽  
Xiudong Sun ◽  
Yongyuan Jiang ◽  
Chunfeng Hou
Keyword(s):  
Information Content ◽  
Saliency Detection ◽  
Visual Saliency ◽  
Visual Saliency Detection

scholarly journals SAMM: Surroundedness and Absorption Markov Model Based Visual Saliency Detection in Images

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 71422-71434 ◽  
Author(s):  
Zhenguo Gao ◽  
Naeem Ayoub ◽  
Danjie Chen ◽  
Bingcai Chen ◽  
Zhimao Lu
Keyword(s):  
Markov Model ◽  
Saliency Detection ◽  
Visual Saliency ◽  
Model Based ◽  
Visual Saliency Detection
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