Portrait photograph automatic background blurring method based on saliency detection

A background blurring and significant technology, applied in the field of automatic background blurring of portrait photos, can solve the problems of not calculating the foreground portrait area, portrait area blurring, etc.

Inactive Publication Date: 2018-09-21
FUZHOU UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The algorithm proposed by Chen et al. does not calculate the boundary between the foreground portrait area and the background, which will cause part of the portrait area to be blurred

Method used

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  • Portrait photograph automatic background blurring method based on saliency detection
  • Portrait photograph automatic background blurring method based on saliency detection
  • Portrait photograph automatic background blurring method based on saliency detection

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Embodiment Construction

[0053] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0054] The present invention provides a method for automatically blurring the background of portrait photos based on saliency detection, such as figure 1 and figure 2 shown, including the following steps:

[0055] Step S1: The portrait image is segmented into N superpixels using the linear spectral clustering (LSC) superpixel segmentation algorithm, and then the saliency value of each superpixel is calculated using the improved saliency optimization algorithm. Specifically include the following steps:

[0056] Step S11: For any portrait image I, use the linear spectral clustering superpixel segmentation algorithm to segment it into N superpixels Get the set of superpixel segmentation markers Each superpixel segmentation label l i Corresponding to the set of all pixels contained in the i-th superpixel, i is the superpixel segmentation la...

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Abstract

The invention relates to a portrait photograph automatic background blurring method based on saliency detection. The method comprises the following steps: 1) segmenting a portrait image into N superpixels through a linear spectrum clustering superpixel segmentation algorithm, and calculating a saliency value of each superpixel through an improved saliency optimization algorithm; 2) marking the superpixel, the saliency value of which is greater than an adaptive threshold, as a foreground area through an Otsu method, marking the superpixel, the saliency value of which is smaller than a fixed threshold, as a background area, and marking the rest superpixels as an unknown area to obtain a superpixel scale marked three-parted graph; 3) carrying out segmentation on the marked three-parted graphto obtain a portrait area boundary by utilizing a superpixel scale GrabCut algorithm; and 4) carrying out blurring on the background area through a fast guided filtering algorithm first, and then, selectively carrying out detail enhancement on the foreground area according to the saliency detection result to obtain a background blurring effect. The method can quickly carry out background blurringby only relaying on a single portrait image, and improves the background blurring effect.

Description

technical field [0001] The invention relates to the fields of image and video processing and computer vision, in particular to a method for automatically blurring the background of portrait photos based on saliency detection. Background technique [0002] With the rapid popularization of smart devices, most of the photos taken by smart phones are portrait photos. Due to the lack of professional photo post-processing technology, most smart device users have a strong demand for automatic beautification of portrait photos in the later stage. Among them, background blur technology, also known as shallow depth of field technology, is a beautification method used to highlight the subject of photography and express visual beauty in a layered manner. At present, with the rapid development of smart device hardware, the realization of background blur technology mainly relies on two hardware foundations, one is the rear dual camera of the smart device, and the other is the front depth...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T3/00G06T7/10G06T7/13G06T7/136G06T7/194H04N5/232
CPCG06T3/0012G06T7/10G06T7/13G06T7/136G06T7/194G06T2207/10004G06T2207/20024H04N23/80
Inventor 牛玉贞苏超然陈羽中
Owner FUZHOU UNIV
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