| Seeding uniformity is an important factor to evaluate performance and quality of seeders. The comprehensive seeding accuracy testing method proposed in this dissertation to test performance of precision seeder, grain drill seeder, hill-drop planter, seeding monomer, and seed sowing device is an integrative one with technology of computer vision, patter recognition, and automatic control. The core task is application of computer vision techniques in seeding accuracy dynamical testing. Accurate and reliable seeding accuracy test and automatic control of the test-bed are realized. Main study contains:1 A seeder performance test system based on computer vision is built. Precision seeder, grain drill seeder, hill-drop planter, seeding monomer, and seed sowing device for the first time are realize to be tested on one comprehensive test-bed, and at the same time, hard problem of evaluating seeding accuracy from seed kernel space interval is solved. Test results are accurate, reliable and can be traced to the source.2 Construction method of dynamical image acquisition is studied. Field by field and frame absent image acquisition method is used to remove redundant information and saving computer memory. The three primary color channels of color image are separately captured to the image acquisition board by using special hardware and software technology, therefore, three lines of seeds are parallel captured. Contrastive test is done to compare advantage and disadvantage of threshold chosen method, which can either be chosen from trying or iteration, and predefined threshold chosen is selected, which result in lessen processing time. Region labeling using sequential algorithm and seed object recognition are studied, and then the center of a region is calculated.3 Sequential images matching and splicing technology is studied. Begin with real-time requirement of dynamical testing, image splicing problem is further researched and principle of image splicing is expounded. A new sequential images sub-splicing method is proposed, which based on features of markers and aimed at looking for the same markers in overlapped area of two adjacent images to finish the splicing task. No real image coalescence is done, but the redundant information is diminished, so the two adjacent images are considered well spliced. Big marks are interlaced with small ones to realize accurate image sub-splicing in real situation. Influence of the width of overlapped area on image splicing is studied and its width setting mode is given.4 Construction of the illumination system and camera calibration means are researched. Illumination system construction of computer vision system is studied and a double line space crossing illumination system is built, which results in effective settlement of disparity between illumination system and image acquisition in moving object testing problem. Data accuracy when using three cameras to capture information is further researched, and three cameras system error module and calibration method are determined.5 Hole centers location and hole distance measuring technology are studied. Overlapped seeds are separated by certain algorithm. The key problem in hole-drill planter test is locating of holes centers,which is solved by using geometry moments of discrete masses. And then the holes distance is calculated from holes centers with fairly high precision. Sends scatter state is observed. Overlapped seeds are recognized based on morphological and series connection and parallel connection seeds are defined to effectively separate overlapped seed.6 Automatic control technology of the test-bed is studied. System is coordinated controlled based on serial communication between the computer and PLC. The followed variables are controlled: the rotational speed of the seeding device driven draft, the operation of the converter, stability and speed of the convey belt, and inclination of the test platform, which is done to simulate actual working condition of seeder.Measuring error is overall analyzed. Fo...
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