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Visual saliency detection method with fusion of region color and HoG (histogram of oriented gradient) features

A detection method and color feature technology, applied in the field of computer vision, can solve problems such as highlighting local contours, low resolution, and insensitivity to significant differences in textures

Inactive Publication Date: 2015-04-22
海宁鼎丞智能设备有限公司
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  • Application Information

AI Technical Summary

Problems solved by technology

These methods simulate human eye movement and track the focus of the eye. They have important research value in biology, but there are obvious deficiencies: low resolution, highlighted local outlines, and lack of complete regional awareness
However, the above methods are based on regional color and are not sensitive to significant differences in texture.

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  • Visual saliency detection method with fusion of region color and HoG (histogram of oriented gradient) features
  • Visual saliency detection method with fusion of region color and HoG (histogram of oriented gradient) features
  • Visual saliency detection method with fusion of region color and HoG (histogram of oriented gradient) features

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Embodiment Construction

[0067] The present invention will be further described below in conjunction with accompanying drawing.

[0068] Such as figure 1 As shown, the specific steps of a visual saliency detection method that fuses region color and HoG features are as follows:

[0069] Step (1): Use the color transformation method to extract the input image in the Lab space l color components, a color component maps and b Color component map; the color transformation method described is a mature technology.

[0070] Step (2): Using the SLIC superpixel clustering method, the input image is divided into a plurality of disjoint and approximately equal superpixel regions; the SLIC superpixel clustering method was proposed by R. Achanta et al. [1] .

[0071] Step (3): According to the result of step (2), calculate the color feature of each superpixel region, specifically:

[0072] For the superpixel region r i , whose color features are determined by the superpixel region r i The color mean vecto...

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Abstract

The invention relates to a visual saliency detection method with fusion of region color and HoG (histogram of oriented gradient) features. At present, the existing method is generally based on a pure calculation model of the region color feature and is insensitive to salient difference of texture. The method disclosed by the invention comprises the following steps of: firstly calculating a color saliency value of each pixel by analyzing color contrast and distribution feature of a superpixel region on a CIELAB (CIE 1976 L*, a*, b*) space color component diagram of an original image; then extracting an HoG-based local rectangular region texture feature on an RGB (red, green and blue) space color component diagram of the original image, and calculating a texture saliency value of each pixel by analyzing texture contrast and distribution feature of a local rectangular region; and finally fusing the color saliency value and the texture saliency value of each pixel into a final saliency value of the pixel by adopting a secondary non-linear fusion method. According to the method disclosed by the invention, a full-resolution saliency image which is in line with sense of sight of human eyes can be obtained, and the distinguishing capability against a saliency object is further stronger.

Description

technical field [0001] The invention belongs to the field of computer vision, and specifically relates to a visual saliency detection method that integrates the features of regional color contrast and gradient direction histogram (the English abbreviation "HoG" is used hereinafter to replace it). Background technique [0002] Visual salience is defined as visual unpredictability, scarcity. Supported by the related theory of human visual attention, visual saliency models provide a fast and efficient method as an important preprocessing mechanism in computer vision and image processing. [0003] Current research results show that most visual saliency models are based on a bottom-up process driven by underlying features. Among them, the work with far-reaching significance is the feature fusion theory proposed by L. Itti et al. In their model, color, brightness, and orientation features are extracted separately from the input image, the geographical feature map is annotated, a...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/40
Inventor 周文晖宋腾孙志海张桦韦学辉
Owner 海宁鼎丞智能设备有限公司
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