In the daily driving process, road potholes pose a great threat to traffic safety. However, the actual road potholes are often irregular and the background is complex. So, it is difficult to accurately measure the volume of potholes. In this paper, a method for measuring the volume of road potholes based on three-dimensional point clouds is presented. First, binocular vision is used to obtain 3D point cloud data of the pothole, and the segmented pothole point clouds are projected onto the coordinate plane established by the road surface. Then, we triangulate projection points on the coordinate plane. Finally, restore these points to the true elevation points to generate triangular prism, and calculate the volume of a single triangular prism one by one. The accuracy and effectiveness of this algorithm are verified by experiments.
Road potholes affect comfort, safety, traffic condition and vehicle stability. Accurately detecting these potholes is vital for assessing the degree of pavement distress and developing road maintenance plan accordingly. This paper proposes a simple and effective pothole detection method based on 3D point cloud segmentation. Using binocular stereo vision to acquire 3D point clouds, fitting the pavement plane and then eliminating it from the 3D point clouds of road scene, we could roughly extract the pothole. K-means clustering and region growing algorithms were adopted to extract the potholes precisely. The experimental results demonstrate that our proposed method has a very good segmentation effect on scenes involving plane and target object.
Remote video monitoring has become increasingly important for monitoring the security of purpose locations. Most of the surveillance system needs high-definition (HD) video. Multi-channel HD video data real-time transmission and data transmission security are two of the factors restricting the development of remote monitoring system. To solve this problem, this paper presents a new high-definition video surveillance system program, high-definition camera video by video relay input to high-definition video encoder, high-definition video encoder for data compression, compressed data input HD video decoder after long-distance transmission by Gigabit Ethernet, high-definition video decoder to decode the compressed data, then the video data input DVR after decompression, the video data may be stored and can be displayed in real time. A balanced algorithm is used to adapt transmission bandwidth and a iterative algorithm is used to smooth out random packets loss rate. After testing, the system can transmits five hundred compressed video data and have excellent expansibility; data transmission is very secure because of independent Ethernet and encryption algorithm.
KEYWORDS: 3D modeling, Cameras, 3D vision, Calibration, Satellites, Reconstruction algorithms, Visual process modeling, Detection and tracking algorithms
In this paper, we propose an automatic method for high precision measurement and 3D reconstruction of non-cooperative spacecraft based on binocular vision. The Zhengyou Zhang’s calibration method was implemented to calibrate the camera’s internal and external parameters; the 8-point algorithm was adopted to compute the fundamental and essential matrix between the cameras; we got the relative position of binocular camera by the method of the SVD of essential matrix; a stereo matching algorithm depending on the Semi-Global Matching was adopted for disparity map. Subsequently, the cloud information of world points was calculated through least square method. In our experiment, a complex outdoor scene was used. We made a satellite model which has the same size of the real one. To get the accurate position and angle of the spacecraft, the ellipse marks on the spacecraft was exacted effectively under three constraints. The experimental results show that the spacecraft model can be reconstructed accurately by our method. The method contributes the error rate of 1% for the test length and 3% for the test angle in 1 meter.
KEYWORDS: 3D metrology, 3D modeling, 3D image processing, 3D acquisition, 3D image reconstruction, Image processing, 3D vision, Statistical methods, Statistical analysis
Measurement of 3D scene from image sequences is necessary for many computer vision applications. In this paper, we identify the volumetric scene reconstruction as a critical issue for target measurement and use the statistical method to estimate the size of the reconstructed target. The proposed approach unifies the view volume in volumetric scene reconstruction while we only know the location information of the camera relative to the target in elliptical orbit. Experimental results on elliptical orbit with 200 meters long axis and 100 meters short axis illustrate that the average error is about 44 millimeters, which meets the accuracy requirement of general measurement.
In this paper, a road detection algorithm from the low illumination remote sensing images is proposed. First, the top-hat transform is used to enhance the edge information in low illumination images. Next, a road detection method based on parallel lines is proposed to detect the parallel characteristics of the two edges of the road. The experiment results show that the proposed algorithm can detect the road information effectively and precisely.
The traditional tone mapping algorithm for the display of high dynamic range (HDR) image has the drawback of losing the impression of brightness, contrast and color information. To overcome this phenomenon, we propose a new tone mapping algorithm based on dividing the image into different exposure regions in this paper. Firstly, the over-exposure region is determined using the Local Binary Pattern information of HDR image. Then, based on the peak and average gray of the histogram, the under-exposure and normal-exposure region of HDR image are selected separately. Finally, the different exposure regions are mapped by differentiated tone mapping methods to get the final result. The experiment results show that the proposed algorithm achieve the better performance both in visual quality and objective contrast criterion than other algorithms.
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