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Automatic detection method of salient object based on salience density and edge response

An edge response and automatic detection technology, which is applied in image data processing, instruments, calculations, etc., can solve the problems of low detection accuracy of salient objects and does not consider the edge attributes of salient objects, etc., and achieve the effect of improving accuracy

Active Publication Date: 2013-07-10
中数(深圳)时代科技有限公司
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Problems solved by technology

[0003] In order to solve the problem that the accuracy of salient object detection is not high due to the use of only one attribute of saliency without considering the edge attributes of salient objects in the existing salient object detection method, the present invention provides salient object automatic detection based on saliency density and edge response method

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  • Automatic detection method of salient object based on salience density and edge response
  • Automatic detection method of salient object based on salience density and edge response
  • Automatic detection method of salient object based on salience density and edge response

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specific Embodiment approach 1

[0013] Specific implementation mode one: the following combination figure 1 To illustrate this embodiment, the salient object automatic detection method based on saliency density and edge response described in this embodiment includes the following steps:

[0014] Step 1. Calculate and generate a saliency map S of the input image according to a saliency calculation method combining global color contrast and color space distribution;

[0015] Step 2. On the saliency map S, use a set of Gabor filters to generate an edge response map E;

[0016] Step 3. Use the branch-and-bound algorithm that maximizes saliency density and edge response to search for globally optimal sub-windows containing salient objects in the input image ;

[0017] Step 4: Locate the optimal sub-window in Step 3 As input, initialize the GrabCut image segmentation method;

[0018] Step 5. Run the GrabCut image segmentation method to automatically extract salient objects with very good edges.

[0019] The...

specific Embodiment approach 2

[0020] Specific embodiment 2: This embodiment is a further description of specific embodiment 1. In step 1, the calculation formula used to generate the saliency map method of the input image according to the regional saliency method combined with global color contrast and color space distribution is:

[0021] S ( r k ) = 1 2 ( N ( S sd ( r k ) ) + N ( S rc ( r k ) ) ) ; ...

specific Embodiment approach 3

[0023] Specific embodiment three: this embodiment is a further description of specific embodiment one. In step two, a group of Gabor filters are used on the saliency map S to generate the method for edge response map E. The calculation formula used is:

[0024] E ( p ) = max i = 1 15 | ( S * G i ) ( p ) | 2 ; - - - ( 2 )

[0025] In the formula, E(p) represents the edge response corresponding to pixel p, the symbol * represents the convolution operation...

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Abstract

The invention provides an automatic detection method of a salient object based on salience density and edge response, and relates to a method for automatically detecting the salient object, solving the problems of the convectional salient object detection method that only one attribute that is the salience is utilized, but the edge attribute of the salient object is not taken into account, therefore, the detection accuracy of the salient object is relatively low. The automatic detection method of the salient object based on the salience density and the edge response comprises the following steps of: calculating and generating a salient map S of an input map according to the regional salience calculation method in combination of the global color comparison and the color space distribution; generating an edge response map E on the salient map S by utilizing a group of Gabor filters; efficiently searching a global optimal sub-window containing the salient object in the input map by utilizing the maximized branch-and-bound algorithm of the salience density and the edge response; adopting the obtained optimal sub-window as the input; initializing the GrabCut graphic cutting method; carrying out the GrabCut graphic cutting method; and automatically extracting the salient object with a good edge. The automatic detection method is applicable to the image processing field.

Description

technical field [0001] The invention relates to a method for automatic detection of salient objects. Background technique [0002] The human visual system always automatically focuses attention on salient objects, and this ability allows us to allocate the limited processing resources of the human brain to important parts of the image. Salient object detection has many successful applications in machine vision. The existing salient object detection methods can be divided into two categories: the first type of method tends to find the most likely rectangular box containing the salient object; the second type of method tends to Apply object segmentation methods to obtain salient objects with nice edges. However, the above two types of methods only use the property of saliency (the property possessed by salient objects). In the process of saliency calculation, a large amount of original image information that may be helpful for detecting salient objects is inevitably lost, an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 牛夏牧景慧昀韩琦李琼王莘
Owner 中数(深圳)时代科技有限公司
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