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Research of 3D Binocular Vision Measurement Technology
Author: ChenJiTang
Tutor: XuDu
School: Guangdong University of Technology
Course: Communication and Information System
Keywords: Three-dimensional Measurement Camera Calibration Image Matching Bbinocular Vision Parallel Rectify Corner Extraction
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 192
Quote: 1
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Abstract
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Computer vision is an emerging technology, as a non-contact measurement technology based on computer vision.It got the advanced of high precision, high efficiency, low cost and so on,It has broad application prospects. Stereo binocular vision is an important branch of computer vision. Taking photo form different locations with one camera or take photo using two camera.So as to obtained the parallax,and use the parallax to calculate the 3d coordinates.Because of binocular measuring both can satisfy the measurement of real-time, and cost price much smaller than other methods are. So, binocular vision application in the measurement is more widely. In addition to the actual object measurement, in other areas outside it also get some progress. To measure by binocular vision, we only need extraction of essential feature from two corresponding image to get the 3d coordinate. The Information is less and can calculate fast.It’s helpful for improving precision, especially suitable for dynamic situation.Along with the development of computer and robot.Binocular research is also gradually in-depth, from the former triangle theorem to the rays theorem.It optimize the search method of matching point. Achieved quickly match scheme and simplified formula of reduction depth.Binocular vision is now generally applied to the 3d positioning device, provide 3d trajectory information for CNC machining, and also provide 3d information for a machine assembly hand.. Currently popular research applications including body feeling games, virtual screen (it can control screen in the air), machine navigate,etc.This paper study the corner extraction, image pre-processing, cmera calibration, feature extraction, Stereo matching, parallel correction and target space positioning aspects. This paper mainly do the following:1. design research work that can keep original Edge information and also to remove noise.2. programe a sofeware to mease flatness;3. programe a sofeware to do the calibration and calculate depth.This paper consists of six chapters.Chapter 1 is the introduction part, mainly introduced the computer vision technology research at home and abroad. Then, starting from the image preprocessing, we optimize the photo, so as to make the image features more apparent, extracted with classical Harris operator to get corner subpixel information. And introduces several classic calibration method, analyzes the advantages and disadvantages, and give the detailed algorithm process.Chapter 2 mainly presents the computer vision system, image processing, binocular stereo vision and 3-D reconstruct technology.Chapter 3 translates optical physical properties to mathematical model, and introduces the concept of outside parameters and inside parameters participation. establish a relationship for physical world and Mathematical model, This paper introduces some typical calibration algorithm, and give detailed algorithm process. Establish foundation For the 3d reduction.Chapter 4 explains general image preprocessing method, the purpose is to make feature more prominent. Providing matching accuracy for the fourth chapter..Chapter 5 introduces several description method and its matching method, then Emphasis on sift algorithm, and give the Matching results.Chapter 6 emphasized parallel correction method, using the calibration results of the second chapter to do the parallel correction.After parallel correction,it can simplify the Depth measurement equation.In this chapter we give examples of 3d reconstruction, measure the length of the object. Experimental proof calibration results are reliable, and 3d it can restore information accurately.
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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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