The Study Of Logistics Vehicle Type Recognition Based On Differential Geometry Method

Nowadays, more and more industries take good service as the most significantcontent of management. As a result, various industries have invested a lot of itsmanpower and resources. Those industries strive for the further improvement of theirservice levels, and an enhancement of their overall competitiveness. Thisphenomenon happens mainly in the logistics industry. Logistics industry is aspecialized service sector; it achieves its goal of service through the vehicle transport.“How to achieve transparency in the transport process and meet the requirements ofcustomer” has become a key issue of logistics industry. In face, the effective way tosolve this problem is to build an effective vehicle recognition system. But the currentprice of the vehicle recognition system is very expensive, which makes a lot oflogistics enterprises feel helpless. Especially for those small or medium sized logisticsenterprises, they are more concerned with the benefits of their cost. Therefore, if thereis an economical vehicle recognition system, it certainly will bring a lot ofconvenience to small and medium sized logistics enterprises. Meanwhile, if we candesign a vehicle recognition system which is specifically for the logistics vehicle, itwill bring a huge improvement for the transport services of logistics enterprisesundoubtedly.This thesis will apply the differential geometry to identify the types of vehicles.Specifically, first, we use computer systems to accomplish the task of logisticsvehicles’ image acquisition and contour segmentation. Then, we will use the modelthat established by the writer to calculate the curvature of all characteristic points andsimilarity distance. Afterwards, we will store the datum in the database. When we runthe identification system, we will the matched model parameters with the data in thedatabase. If the matching is successful, it will analyze the type of the vehicle, and wecan achieve the goal of vehicle recognition.The general idea of the paper: The first chapter is the introduction. It mainly introduces the significance of the research of the vehicle identification system,research status at home and abroad and the search methods. The second chapter ismainly talks about literary review of relevant theories. It focuses on the emergenceand development of differential geometric; existing principle of vehicle recognitionsystem; the possibilities of apply differential geometry in vehicle recognition system.The third chapter focuses on the extraction of vehicle profile and the classification oflogistics models. This chapter includes the acquisition of vehicle image, grayprocessing, enhancement of gray processing, extraction of contour and otherprocesses. The fourth chapter is mainly about the storage of each model parameter,matching method and the establishment of vehicle recognition system. In this paper,the primary model parameter is the curvature and the relative distance between eachtwo points. Recognition model using BP neural network model to conductidentification; and demonstrates the complexity and robustness of this approach. Thefifth chapter is mainly about the establishment a database. This database is used tostore the data of vehicle types. The sixth chapter is the summary outlook of this thesis.It analyzes the innovation and deficiencies of this paper, and points out the subsequentresearch direction.