JOURNAL ARTICLE

Center-focus global contrast saliency detection

Abstract

Saliency detection has a great significance in improving image analysis and processing techniques. In this paper, we propose a center-focus global contrast saliency detection method. First, we achieve the weight of focus-center feature map from frequency domain and get the salient center by weighted coordinates; Secondly we calculate the Euclidean distance between the image of each pixel and the saliency center for generating the focus-center feature map; Then the image is segmented by SLIC, and taking segments as a unit build the color global contrast feature map; Finally three feature maps are normalized and integrated as the saliency map. The saliency detection method proposed in this paper compare with 7 saliency detection methods by the public database Achtana1000 [12] and our method have higher precision and recall than others.

Keywords:
Artificial intelligence Computer science Feature (linguistics) Focus (optics) Computer vision Contrast (vision) Pattern recognition (psychology) Pixel Salient Feature extraction Feature detection (computer vision) Saliency map Precision and recall Center (category theory) Image (mathematics) Image processing

Metrics

1
Cited By
0.17
FWCI (Field Weighted Citation Impact)
19
Refs
0.60
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Visual Attention and Saliency Detection
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Olfactory and Sensory Function Studies
Life Sciences →  Neuroscience →  Sensory Systems
Image and Video Quality Assessment
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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