scholarly journals An Improved Sum of Squared Difference Algorithm for Automated Distance Measurement

2021 ◽  
Vol 9 ◽  
Author(s):  
Yue Lin ◽  
Yixun Gao ◽  
Yao Wang

In recent years, with improvement of photoelectric conversion efficiency and accuracy, photoelectric sensor was arranged to simulate binocular stereo vision for 3D measurement, and it has become an important distance measurement method. In this paper, an improved sum of squared difference (SSD) algorithm which can use binocular cameras to measure distance of vehicle ahead was proposed. Firstly, consistency matching calibration was performed when images were acquired. Then, Gaussian blur was used to smooth the image, and grayscale transformation was performed. Next, the Sobel operator was used to detect the edge of images. Finally, the improved SSD was used for stereo matching and disparity calculation, and the distance value could be obtained corresponding to each point. Experimental results showed that the improved SSD algorithm had an accuracy rate of 95.06% when stereo matching and disparity calculation were performed. This algorithm fully meets the requirements of distance measurement.

2021 ◽  
Vol 10 (4) ◽  
pp. 234
Author(s):  
Jing Ding ◽  
Zhigang Yan ◽  
Xuchen We

To obtain effective indoor moving target localization, a reliable and stable moving target localization method based on binocular stereo vision is proposed in this paper. A moving target recognition extraction algorithm, which integrates displacement pyramid Horn–Schunck (HS) optical flow, Delaunay triangulation and Otsu threshold segmentation, is presented to separate a moving target from a complex background, called the Otsu Delaunay HS (O-DHS) method. Additionally, a stereo matching algorithm based on deep matching and stereo vision is presented to obtain dense stereo matching points pairs, called stereo deep matching (S-DM). The stereo matching point pairs of the moving target were extracted with the moving target area and stereo deep matching point pairs, then the three dimensional coordinates of the points in the moving target area were reconstructed according to the principle of binocular vision’s parallel structure. Finally, the moving target was located by the centroid method. The experimental results showed that this method can better resist image noise and repeated texture, can effectively detect and separate moving targets, and can match stereo image points in repeated textured areas more accurately and stability. This method can effectively improve the effectiveness, accuracy and robustness of three-dimensional moving target coordinates.


2012 ◽  
Vol 490-495 ◽  
pp. 711-715
Author(s):  
Alin Hou ◽  
Ying Geng ◽  
Xue Cui ◽  
Wen Ju Yuan ◽  
Feng Guang Shi

The method of distance measurement based on binocular stereo vision is presented in this paper. The model of camera imaging is established and the process of camera calibration is described. Interior and external parameters of two cameras are calculated by HALCON. The system of visual measurement is fabricated. The parallax measurement of the image pairs is accomplished. The simulation experiments of distance measurement have been done and the calculated results can be in accordance with the actual distance.


10.5772/50921 ◽  
2012 ◽  
Vol 9 (1) ◽  
pp. 26 ◽  
Author(s):  
Xiao-Bo Lai ◽  
Hai-Shun Wang ◽  
Yue-Hong Xu

To acquire range information for mobile robots, a TMS320DM642 DSP-based range finding system with binocular stereo vision is proposed. Firstly, paired images of the target are captured and a Gaussian filter, as well as improved Sobel kernels, are achieved. Secondly, a feature-based local stereo matching algorithm is performed so that the space location of the target can be determined. Finally, in order to improve the reliability and robustness of the stereo matching algorithm under complex conditions, the confidence filter and the left-right consistency filter are investigated to eliminate the mismatching points. In addition, the range finding algorithm is implemented in the DSP/BIOS operating system to gain real-time control. Experimental results show that the average accuracy of range finding is more than 99% for measuring single-point distances equal to 120cm in the simple scenario and the algorithm takes about 39ms for ranging a time in a complex scenario. The effectivity, as well as the feasibility, of the proposed range finding system are verified.


2013 ◽  
Vol 415 ◽  
pp. 361-364
Author(s):  
Hui Yu Xiang ◽  
Zhe Li ◽  
Jia Jun Huang ◽  
Baoan Han

Binocular stereo matching is a hot and difficult problem in machine vision. In this paper, based on the matching method of Halcon which is visual software perform image matching. First, performing binocular stereo vision system calibration, based on the calibration results acquired the epipolar standard geometric structure. Then, image matching researched under this structure. At last, using ncc matching algorithm, through comparing the different parameters matching window obtain ideal match results. Experiments prove that this method not only can effectively shorten matching time, but also can achieve higher matching accuracy.


Optik ◽  
2020 ◽  
Vol 207 ◽  
pp. 164488 ◽  
Author(s):  
Zhaoxin Wang ◽  
Jiang Yue ◽  
Jing Han ◽  
Yong Jin ◽  
Baoming Li

2019 ◽  
Vol 252 (5) ◽  
pp. 052051
Author(s):  
Xiyan Sun ◽  
Yingzhou Jiang ◽  
Yuanfa Ji ◽  
Wentao Fu ◽  
Suqing Yan ◽  
...  

2013 ◽  
Vol 303-306 ◽  
pp. 313-317 ◽  
Author(s):  
Zhong Wei Zhou ◽  
Min Xu ◽  
Wei Fu ◽  
Ji Zeng Zhao

The goal of this paper is to present a method for object tracking and positioning based on stereo vision in real time. The method effectively combined stereo matching algorithm with object tracking algorithm, and calculated the spatial location information of the object by using binocular stereo vision while the object is being tracked. The stereo matching used dynamic programming, image pyramids and control points modification algorithm, and the object tracking mainly utilized CamShift algorithm in this paper. The experimental results have confirmed that the proposed method realized real-time tracking for moving object, accurate calculating for the object three-dimensional coordinates, which meet the applied needs of servo follow-up system.


2014 ◽  
Vol 610 ◽  
pp. 209-215 ◽  
Author(s):  
Rong Xiang ◽  
Huan Yu Jiang ◽  
Yi Bin Ying

Accuracy three dimensional coordinates of fruits and vegetables are very important to harvesting robots to harvest fruits and vegetables correctly. To decrease the measurement errors of the y coordinates of tomatoes, we analyzed the measurement errors of y coordinate acquired using binocular stereo vision based on three stereo matching methods. These three stereo matching methods were centroid-based, area-based, and combination stereo matching methods. After stereo matching, the three dimensional coordinates of tomatoes could be acquired based on the triangle ranging principle. Tests of 225 pairs of stereo images of three plastic balls used as normal balls acquired at the distances from 300 to 1000 mm showed that the ranges of the measurement errors of y coordinate acquired based on three stereo matching methods changed with the image acquisition distances obviously. Moreover, the measurement errors of y coordinate appeared linear decreasing trends approximately. Therefore, binary linear regression models were set up to reduce the ranges of the measurement errors of y coordinate of three balls. These models were used as correction models of the measurement values of y coordinate and were helpful to reduce the measurement errors of y coordinate. However, there were owe correction and overcorrection conditions when the image acquisition distances were smaller and larger than 750 mm separately. Then, the correction models based on piecewise binary linear regression were used to solve this problem. The ranges of the measurement errors of y coordinate were reduced further. Tests of 225 pairs of stereo images of three tomatoes acquired at the distances from 300 to 1000 mm showed that the ranges of the measurement errors of y coordinate acquired based on three stereo matching methods were separately from [-20.9, -6.6], [-19.9, -3.44], [-19.9, -3.48] mm to [-6.84, -0.06], [-5.84, -0.82], [-5.85, -0.83] mm after the correction using the piecewise binary linear regression models. It proved that the piecewise binary linear regression models were helpful to reduce the measurement errors of y coordinate in three dimensional localization of tomatoes using binocular stereo vision.


Sign in / Sign up

Export Citation Format

Share Document