Research On The Key Techniques Of Grain Quantity Measurement Based On Laser Ranging

Grain security is closely related to social harmony, political stability, sustained economicdevelopment. In our country, the reserved grain warehouses are distributed in different regionsand have large scale and their capacity is large. Intelligent audit of grain quantity is the key ofthe automatic reserved grain supervision all the time. But due to the limitations of technology,present researchers have failed to solve this problem effectively at home and abroad.In this paper, in view of the current grain audit method consuming a large amount ofmanpower and financial resources, the nondestructive measurement method of grain quantitybased on laser ranging technology is presented. The research designs and develops amultithreading data acquisition and processing software system and the research emphasisincludes grain boundary identification,3D coordinates computation method of the position of thelaser spot on the grain surface and grain volume calculation. The major work is as follows:(1) A indirect identification method of grain boundary by using the BP algorithm to identifythe categories of grain is proposedIn this system, grain volume is calculated by use of the3D coordinates of the points on thegrain surface, so the grain boundary needs to be identified.①Double hidden layers BP network is designed to recognize the categories of grain. Onthe base of analyzing the structure and algorithm of BP network, according to the requirementsof this project, the12-28-20-1network structure is determined by training and testing. To theresearch object (grain pile) of this thesis, the categories of grain cannot be identified by the shapeof the cereal kernel. In view of the problem, the color moment vectors of the grain image withoutbackground is used for the feature vectors to train and test BP network so that BP network canidentify the categories of grain participating in training. The recognition of corn was realized, theexperiment shows that the correct recognition rate is high.②The boundary identification of corn pile is achieved. Extract line-by-line the colormoment feature vector of the3*3window beginning with the one corner of the corn image withthe background (granary wall) and input it into BP network in turns. BP network judge whether itis corn. If it is corn, the pixels’ gray values of the3*3window are set into0, otherwise255. In theend, binary gray grain boundary image is gotten in which corn region is black and the background is white. The result of grain boundary extraction shows that the grain boundary recognitionmethod proposed in this thesis is feasible.(2) The calculation method of the3D coordinates of laser spot location on the grain surfaceis studiedThe3D coordinates of the laser spot location in the grain boundary are calculated, otherwisenot.①In order to determine the spot location in the grain image, the spot in the grain image isextracted by mean background model method. The experiment result shows that the location andshape of the spot extracted by mean background model method in the spot image are the same asthe location and shape of it in the grain image, so the method is correct.②In order to determine whether the spot is in grain boundary and Delaunay triangulation,the sub-pixel coordinates of the spot center are extracted by curve fitting sub-pixel centerlocalization algorithm based on gravity. The experiment results show that the positioningprecision of this method is higher.③Whether the spot is in grain boundary is judged according to the pixel value of thelocation of the spot center sub-pixel coordinates in the grain boundary image extracted. If thepixel value is0, the spot is in grain boundary and kept to compute the3D coordinates of itslocation; if the pixel value is255, the spot is outside grain boundary and is abandoned. Theexperiment result shows that the judgment that the spot is or not in grain boundary is accurate.④The original calculation method of3D coordinates of the spot location is presented.After the devices are calibrated, by use of the distance measured by the laser rangefinder, therotation angle of the PTZ and the projection of the space point on each axis in the worldcoordinate system, the formulas were derived to calculate the3D coordinates of the spot locationwhen the head’s vertical rotation angle is under four circumstances. The experiment results showthat the calculation formulas of the3D coordinates of the spot position are correct.(3) The grain volume calculation is realizedThe two-dimension Delaunay triangulation is innovatively applied to the3D volumecalculation of grain pile. After a group of spots merged in an image and on the grain surface aredecomposed by two-dimensional Delaunay triangulation, multiple triangles that don’t overlapare gotten. The triangle vertices are spot centers that they correspond to the spots on the grain surface. So the surface of grain is segmented by the triangles, and it is a pentahedron under everytriangle. The volume of the pentahedron is calculated by use of the3D coordinates of the verticesof each triangle, and the sum of the pentahedrons is the total volume of grain. In the laboratory,the volume of corn in the regular container is calculated (the volume of corn is known), theexperiment result shows that the volume error meets the demand of grain supervision.(4) A multithreading data acquisition and processing system is designed and developedTaking VS2008as the development platform, C++language as the development tool, amultithreading data acquisition and processing system is designed and developed. The softwaresystem includes: device control, data acquisition, grain boundary identification, spot extraction,spot center sub-pixel coordinate extraction, the calculation of3D coordinates of the space pointcorresponding to the spot location, Delaunay triangulation, grain volume calculation, filemanagementand so on.In this system, device control and data acquisition is achieved through the serial port, andworkers aren’t needed to go into the granary, so the non-contact nondestructive measurement ofgrain quantity is realized. The volume error is about3%and can meet the managementrequirement of the grain supervision department. This system demands less equipment and itscost is lower, so the cost of supervision and audit can be reduced greatly. This system has broadapplication prospects.