Semantic object dividing method suitable for low depth image

An object segmentation and image technology, applied in image analysis, image enhancement, image data processing, etc., can solve the problems of unsatisfactory algorithm practicability and adaptability

Inactive Publication Date: 2010-08-11
SHANGHAI UNIV
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Problems solved by technology

Many scholars have proposed many classic segmentation algorithms in the field of image segmentation, but relying on traditional image segmentation methods to extract semantic objects from arbitrary images, the practicability and adaptability of the algorithm are not ideal, so the proposed algorithm for a class of images A reliable semantic object segmentation method has become a very necessary research direction

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  • Semantic object dividing method suitable for low depth image
  • Semantic object dividing method suitable for low depth image
  • Semantic object dividing method suitable for low depth image

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Embodiment Construction

[0070] An implementation example of the present invention is described in detail as follows in conjunction with accompanying drawing:

[0071] The semantic object segmentation method based on the low depth of field image of the present invention is programmed on a PC test platform with a CPU of 3.0GHz and a memory of 1024M according to the program block diagram shown in Figure 3, and Figure 6 and Figure 7 show the simulation test results.

[0072] Referring to Figure 2, the semantic object segmentation based on the low depth of field image can segment the objects concentrated in the low depth of field in the image to realize the object extraction. Using the distribution of high-frequency information in different depths of field in the image is different, the focus area is located, and the object segmentation is optimized through a series of algorithms.

[0073] Fig. 3 shows the program flow steps of the overall technical solution of the present embodiment:

[0074] The above-...

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Abstract

The present invention relates to a semantic object segmentation method suitable for low field depth image, which includes: firstly introducing gradient histogram to figure out the distribution of image in the energy space, obtaining an energy focusing significance map in combination with the character of the low field depth map; using the two-sided filter and morphology instrument to rehandle theenergy focusing significance map; and then setting self-adapting threshold value and processing to obtain an initial object mask map, combining with the edge information obtained by canny operator toobtain the corrected object mask, in order to raise the segmentation accuracy of the interesting object; finally using the Bayesian eclosion algorithm to obtain the ideal semantic object segmentationresult, in order to delicately process the complicated image boundary, such as hairs. Accurate segmentation to the interesting object in the field depth scope in the image video sequence.

Description

technical field [0001] The invention relates to a semantic object segmentation method suitable for images with low depth of field, which is completely different from the current method in that, in terms of the accuracy of solving the distribution of the focus area, the energy focus saliency map is obtained through the energy space of the image; at the same time, the method The edge information of the image and the matting algorithm are used to refine the boundary of the object, and the segmentation accuracy of the object is improved. Background technique [0002] Image segmentation is an important issue in the fields of image analysis, pattern recognition and computer vision, and it is also a classic difficult problem. The ultimate goal of image segmentation is to segment objects with specific practical significance, that is, semantic objects. Many scholars have proposed many classic segmentation algorithms in the field of image segmentation, but relying on traditional image...

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Application Information

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Patent Type & AuthorityPatents(China)
IPC IPC(8): G06K9/46G06T7/00G06T5/00
Inventor李伟伟刘志顾建栋韩忠民颜红波
OwnerSHANGHAI UNIV