scholarly journals A New Extension of the Rank Transform for Stereo Matching

2011 ◽  
Vol 2-3 ◽  
pp. 182-187 ◽  
Author(s):  
Ge Zhao ◽  
Ying Kui Du ◽  
Yan Dong Tang
Keyword(s):  
3D Reconstruction ◽  
Transition Zone ◽  
Stereo Matching ◽  
Color Images ◽  
Smooth Transition ◽  
Discriminative Power ◽  
Rank Transform ◽  
Left And Right ◽  
Disparity Maps ◽  
Image Pixels

Stereo matching methods often use rank transform to deal with image distortions and brightness differences prior to matching but a pixel in the rank transformed image may look more similar to its neighbor, which would cause matching ambiguity. We tackle this problem with two proposals. Firstly, instead of using two values 0 and 1,we increase the discriminative power of the rank transform by using a linear, smooth transition zone between 0 and 1 for intensities that are close together. Secondly, we propose a new Bayesian stereo matching model by not only considering the similarity between left and right image pixels but also considering the ambiguity level of them in their own image independently. We test our algorithm on both intensity and color images with brightnesss differences. Corresponding 2D disparity maps and 3D reconstruction results verify the effectiveness of our method.

Engineered Semi-Flexible Composite Mixture Design and Its Implementation Method at Railroad Bridge Approach

2021 ◽  
pp. 036119812110049
Author(s):  
Shuai Yu ◽  
Shihui Shen ◽  
Hai Huang ◽  
Cheng Zhang
Keyword(s):  
Transition Zone ◽  
Structural Adjustment ◽  
Asphalt Mixture ◽  
Vertical Displacement ◽  
Smooth Transition ◽  
Railway Track ◽  
Dynamic Force ◽  
Entire Structure ◽  
Bridge Approach ◽  
Composite Mixture

Considerable variation in the vertical displacement can cause railway tracks’ transition problems at the bridge approach. The vertical displacement gaps can result in amplification of the dynamic force and frequency, and gradually degrade the serviceability of the railway track. Many strategies, focusing on either modifying the track component or making changes to the entire structure, were used to mitigate transition problems. In particular, asphalt concrete underlayment as a structural adjustment method provides additional support to the ballast and protects the subgrade. However, its effect of reducing dynamic impact at the bridge approach is limited because asphalt mixture has a limited range of modulus and cannot make enough adjustments to the entire structure. Therefore, this paper aims to develop an engineered semi-flexible composite mixture (SFCM) design to mitigate the transition problem. The experiment showed that SFCM is a viscoelastic material with a wider modulus range, and its modulus can adjust with its air voids and the concrete slurry content. Track analysis using a 2.5D sandwich model was conducted to simulate the effects of the structure and material on the responses of the railway track under the dynamic loads and determine the arrangement of the transition zone. A four-segment transition zone design was eventually proposed for a special case of bridge approach. This method can be used to develop transition zones for achieving a smooth transition at the bridge approaches.

Symbol recognition system based on 3D stereo vision

2020 ◽  
pp. 1-10
Author(s):  
Linlin Wang
Keyword(s):  
Camera Calibration ◽  
Stereo Vision ◽  
Stereo Matching ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Recognition System ◽  
Symbol Recognition ◽  
Two Dimensional ◽  
Measuring Machine ◽  
Left And Right

With the continuous development of computer science and technology, symbol recognition systems may be converted from two-dimensional space to three-dimensional space. Therefore, this article mainly introduces the symbol recognition system based on 3D stereo vision. The three-dimensional image is taken by the visual coordinate measuring machine in two places on the left and right. Perform binocular stereo matching on the edge of the feature points of the two images. A corner detection algorithm combining SUSAN and Harris is used to detect the left and right camera calibration templates. The two-dimensional coordinate points of the object are determined by the image stereo matching module, and the three-dimensional discrete coordinate points of the object space can be obtained according to the transformation relationship between the image coordinates and the actual object coordinates. Then draw the three-dimensional model of the object through the three-dimensional drawing software. Experimental data shows that the logic resources and memory resources occupied by image preprocessing account for 30.4% and 27.4% of the entire system, respectively. The results show that the system can calibrate the internal and external parameters of the camera. In this way, the camera calibration result will be more accurate and the range will be wider. At the same time, it can effectively make up for the shortcomings of traditional modeling techniques to ensure the measurement accuracy of the detection system.

scholarly journals Vision System of Mobile Robot Combining Binocular and Depth Cameras

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Yuxiang Yang ◽  
Xiang Meng ◽  
Mingyu Gao
Keyword(s):  
Mobile Robot ◽  
3D Reconstruction ◽  
Trajectory Planning ◽  
Stereo Matching ◽  
Vision System ◽  
Depth Camera ◽  
Structural Constraints ◽  
Depth Cameras ◽  
Stereo Cameras ◽  
Binocular Stereo

In order to optimize the three-dimensional (3D) reconstruction and obtain more precise actual distances of the object, a 3D reconstruction system combining binocular and depth cameras is proposed in this paper. The whole system consists of two identical color cameras, a TOF depth camera, an image processing host, a mobile robot control host, and a mobile robot. Because of structural constraints, the resolution of TOF depth camera is very low, which difficultly meets the requirement of trajectory planning. The resolution of binocular stereo cameras can be very high, but the effect of stereo matching is not ideal for low-texture scenes. Hence binocular stereo cameras also difficultly meet the requirements of high accuracy. In this paper, the proposed system integrates depth camera and stereo matching to improve the precision of the 3D reconstruction. Moreover, a double threads processing method is applied to improve the efficiency of the system. The experimental results show that the system can effectively improve the accuracy of 3D reconstruction, identify the distance from the camera accurately, and achieve the strategy of trajectory planning.

A fast stereo matching algorithm for 3D reconstruction of internal organs in laparoscopic surgery

2008 ◽  
Author(s):  
Yoshimichi Okada ◽  
Takeshi Koishi ◽  
Suguru Ushiki ◽  
Toshiya Nakaguchi ◽  
Norimichi Tsumura ◽  
...  
Keyword(s):  
Laparoscopic Surgery ◽  
3D Reconstruction ◽  
Stereo Matching ◽  
Internal Organs ◽  
Matching Algorithm

scholarly journals A comparison between a white LED confocal imaging system and a conventional flash fundus camera using chromaticity analysis

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Valentina Sarao ◽  
Daniele Veritti ◽  
Enrico Borrelli ◽  
Srini Vas R. Sadda ◽  
Enea Poletti ◽  
...  
Keyword(s):  
Imaging System ◽  
Color Images ◽  
Confocal Imaging ◽  
Fundus Images ◽  
White Led ◽  
Discriminative Power ◽  
High Quality ◽  
Fundus Camera ◽  
Clear Shift ◽  
Color Rendering

Abstract Background Conventional flash fundus cameras capture color images that are oversaturated in the red channel and washed out in the green and blue channels, resulting in a retinal picture that often looks flat and reddish. A white LED confocal device was recently introduced to provide a high-quality retinal image with enhanced color fidelity. In this study, we aimed to evaluate the color rendering properties of the white LED confocal system and compare them to those of a conventional flash fundus camera through chromaticity analysis. Methods A white LED confocal device (Eidon, Centervue, Padova, Italy) and a traditional flash fundus camera (TRC-NW8, Topcon Corporation, Tokyo, Japan) were used to capture fundus images. Color images were evaluated with respect to chromaticity. Analysis was performed according to the image color signature. The color signature of an image was defined as the distribution of its pixels in the rgb chromaticity space. The descriptors used for the analysis are the average and variability of the barycenter positions, the average of the variability and the number of unique colors (NUC) of all signatures. Results Two hundred thirty-three color photographs were acquired with each retinal camera. The images acquired by the confocal white LED device demonstrated an average barycenter position (rgb = [0.448, 0.328, 0.224]) closer to the center of the chromaticity space, while the conventional fundus camera provides images with a clear shift toward red at the expense of the blue and green channels (rgb = [0.574, 0.278, 0.148] (p < 0.001). The variability of the barycenter positions was higher in the white LED confocal system than in the conventional fundus camera. The average variability of the distributions was higher (0.003 ± 0.007, p < 0.001) in the Eidon images compared to the Topcon camera, indicating a greater richness of color. The NUC percentage was higher for the white LED confocal device than for the conventional flash fundus camera (0.071% versus 0.025%, p < 0.001). Conclusions Eidon provides more-balanced color images, with a wider richness of color content, compared to a conventional flash fundus camera. The overall higher chromaticity of Eidon may provide benefits in terms of discriminative power and diagnostic accuracy.

A Disparity Refinement in Stereo Matching based on Mean-shift Segmentation and Spatiotemporal Domain

2020 ◽  
Vol 64 (2) ◽  
pp. 20505-1-20505-12
Author(s):  
Hui-Yu Huang ◽  
Zhe-Hao Liu
Keyword(s):  
Stereo Matching ◽  
Mean Shift ◽  
Disparity Map ◽  
Video Streams ◽  
Segmentation Strategy ◽  
Information Matching ◽  
Color Similarity ◽  
Spatial Domains ◽  
Disparity Maps ◽  
The Cost

Abstract A stereo matching algorithm is used to find the best match between a pair of images. To compute the cost of the matching points from the sequence of images, the disparity maps from video streams are estimated. However, the estimated disparity sequences may cause undesirable flickering errors. These errors result in low visibility of the synthesized video and reduce video coding. In order to solve this problem, in this article, the authors propose a spatiotemporal disparity refinement on local stereo matching based on the segmentation strategy. Based on segmentation information, matching point searching, and color similarity, adaptive disparity values to recover the disparity errors in disparity sequences can be obtained. The flickering errors are also effectively removed, and the boundaries of objects are well preserved. The procedures of the proposed approach consist of a segmentation process, matching point searching, and refinement in the temporal and spatial domains. Experimental results verify that the proposed approach can yield a high quantitative evaluation and a high-quality disparity map compared with other methods.

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