Binocular vision matching cost aggregation optimization method

A technology of matching cost and optimization method, applied in the field of computer vision, to achieve the effect of improving aggregation accuracy and final parallax accuracy, improving final matching accuracy and real-time performance, and improving accuracy

Active Publication Date: 2019-10-08
南京美基森信息技术有限公司
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Problems solved by technology

[0003] Aiming at the problem of parallax accuracy caused by surrounding error points i

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  • Binocular vision matching cost aggregation optimization method
  • Binocular vision matching cost aggregation optimization method
  • Binocular vision matching cost aggregation optimization method

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Embodiment Construction

[0016] The present invention will be further elaborated below in conjunction with the accompanying drawings and specific embodiments.

[0017] like figure 1 As shown, a schematic flowchart of binocular stereo vision matching in the prior art, and its specific algorithm is as follows image 3 First, the census algorithm is used to match the left and right images. The basic idea is to define a rectangular window in the image area, and use this rectangular window to traverse the entire image. Select the center pixel as the reference pixel, and compare the gray value of each pixel in the rectangular window with the gray value of the reference pixel. The pixels whose gray value is less than or equal to the reference value are marked as 0, and the pixels greater than the reference value are marked as 1. , and finally connect them bitwise to obtain the transformed result, which is a binary code stream composed of 0 and 1. The essence of Census transformation is to encode the gray v...

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Abstract

The invention discloses a binocular vision matching cost aggregation optimization method which can be used in the field of computer vision stereo matching. The method comprises the following steps ofmatching left and right images by adopting a census algorithm, calculating the cost of the left image in a corresponding point parallax range in the right image, and obtaining a cost array in each point parallax range; calculating a cost variance in a disparity range of each point, carrying out cost aggregation, eliminating an error cost in combination with a mask scheme, and calculating an aggregation result of each point; and finally, analyzing the correlation of the data in the aggregation, splitting and isolating uncorrelated paths in the cost aggregation process and the data in the same path, and improving the aggregation real-time performance. The whole method can improve the final matching precision and real-time performance.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and mainly relates to a cost aggregation optimization method for binocular vision matching. Background technique [0002] Computer vision is to use various imaging methods to replace the human visual organ as a means of information acquisition and input, and the computer replaces the human brain to complete the processing and interpretation of information. The ultimate goal is to enable computers to observe, recognize, and understand the physical world like humans. It can extract information from images or image sequences, extract the three-dimensional information of the objective world and the shape of objects. In the 1950s, computer vision technology mainly concentrated in the field of two-dimensional image analysis and recognition. In the mid-1960s, Robert of MIT first completed the explanation of the three-dimensional building block world. At the same time, Huffman, Clows and Waltz s...

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Application Information

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IPC IPC(8): G06T7/55
CPCG06T7/55G06T2207/10028G06T2207/20228Y02T10/40
Inventor 霍志坤丁鹏飞蒋桐李行古筝
Owner 南京美基森信息技术有限公司
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