Underwater Dense Stereo Matching Based on Depth Constraint

Yaqian, 李雅倩 Li; Yan-song, 张岩松 Zhang; Haibin, 李海滨 Li; Wenming, 张文明 Zhang; Lu, 贾璐 Jia

doi:10.3788/gzxb20174607.0715001

Cited by 2 publications

(1 citation statement)

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“…On this basis, they proposed an underwater stereo matching method based on color segmentation to obtain a dense disparity map [24]. Ya-Qian L et al [25] proposed a semi-global algorithm for the dense stereo matching of an underwater image based on depth constraint. A relatively high-precision stereo matching image can be obtained by the above two-dimensional search, but this undoubtedly increases the complexity and calculation time of the algorithm.…”

Section: Introductionmentioning

confidence: 99%

A standard expression of underwater binocular vision for stereo matching

Zhuang

Zhang

et al. 2020

Meas. Sci. Technol.

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A camera in an underwater stereo vision system conforms to a multi-layer refraction model, and the perspective projection camera model is invalid. Because the imaging light is refracted, the corresponding pixel does not conform to the traditional polar constraint, and the stereo matching methods must conduct a two-dimensional search. In this paper, a standard expression is proposed to reduce the search space to one dimension. Based on a light field, any specific underwater binocular stereo vision is converted to a standard setup in which the axes of two cameras are parallel and the image is expressed as the light field, the direction information image and the position image. We found and proved that the direction information image conforms to the rule of corresponding rows. With this standard expression, the stereo matching is efficiently conducted and the 3D information can be computed from the disparity map and the position image. In the experiment, an underwater binocular stereo vision system is developed and the proposed method is compared with the traditional method. The results confirm that the proposed method has several advantages of conciseness, correctness, efficiency, and generality.

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Section: Introductionmentioning

confidence: 99%

A standard expression of underwater binocular vision for stereo matching

Zhuang

Zhang

et al. 2020

Meas. Sci. Technol.

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Underwater High-Precision 3D Reconstruction System Based on Rotating Scanning

Xue

Sun

Wang

et al. 2021

Sensors

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This paper presents an underwater high-precision line laser three-dimensional (3D) scanning (LLS) system with rotary scanning mode, which is composed of a low illumination underwater camera and a green line laser projector. The underwater 3D data acquisition can be realized in the range of field of view of 50° (vertical) × 360° (horizontal). We compensate the refraction of the 3D reconstruction system to reduce the angle error caused by the refraction of light on different media surfaces and reduce the impact of refraction on the image quality. In order to verify the reconstruction effect of the 3D reconstruction system and the effectiveness of the refraction compensation algorithm, we conducted error experiments on a standard sphere. The results show that the system’s underwater reconstruction error is less than 0.6 mm within the working distance of 140 mm~2500 mm, which meets the design requirements. It can provide reference for the development of low-cost underwater 3D laser scanning system.

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Underwater Dense Stereo Matching Based on Depth Constraint

Cited by 2 publications

References 0 publications

A standard expression of underwater binocular vision for stereo matching

A standard expression of underwater binocular vision for stereo matching

Underwater High-Precision 3D Reconstruction System Based on Rotating Scanning

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