Method for identifying car type on basis of binary support vector machines and genetic algorithm
A technology of support vector machine and genetic algorithm, applied in the field of pattern classification, can solve the problems of large number of support vector machines, time-consuming, and it is difficult to obtain satisfactory results, so as to improve the efficiency of the algorithm, improve the recognition speed, avoid blindness and low effect of effectiveness
Inactive Publication Date: 2013-01-16
CHANGZHOU UNIV
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However, the existing car model recognition methods have two main disadvantages: 1) The support vector machine network structure is complex, and the number of support vector machines in the network is large, resulting in low classification and prediction efficiency
2) There is still no uniform standard for the selection of support vector machine parameters. In most cases, it is found by experience and trial and error methods, which is not only time-consuming but also difficult to obtain satisfactory results, and it is difficult to promote practical applications
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[0019] Concrete flow chart of the present invention is as figure 1 shown; divided into the following four steps:
[0020] Step 1: Feature information preprocessing.
[0021] In this step, the eigenvalues used for car model identification are selected and normalized.
[0022] Considering the shape characteristics and acquisition difficulty of car models, based on the experience of car model identification and the main distinguishing points of car models, the four characteristics of the car's length, width, height, and wheelbase are mainly selected as eigenvalues.
[0023] Normalize the selected eigenvalues and linearly transform them into the [0,1] interval. The transformation formula is as follows:
[0024]
[0025] Where x is the eigenvalue before normalization, max(x) and min(x) represent the maximum and minimum values of x, respectively, and x' is the eigenvalue after normalization.
[0026] After completing the normalization of the eigenvalues, all the eigenva...
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The invention discloses a method for identifying car type on the basis of binary support vector machines and a genetic algorithm. The method comprises the following steps: normalizing the characteristic values of length, width, height and axle distance of each car to be identified to form characteristic vectors; distributing a binary number to the type of each car, constructing a binary support vector machine network according to the acquired binary numbers, training each binary support vector machine of the acquired binary support vector machine network, and optimizing a penalty parameter c and a kernel function parameter gamma of the binary support vector machine by the genetic algorithm to acquire the optimum parameters c and gamma; and inputting the characteristic vectors into the binary support vector machine network which finishes training, and predicting the binary support vector machine network which finishes training by the optimum parameters c and gamma to identify the type of each car. The vector machines of the binary support vector machine network are reduced, so that the number of the required support vector machines is far less than that of the required support vector machines in the similar method, the identification speed is increased and the algorithm efficiency is improved.
Description
technical field [0001] The invention belongs to the technical field of pattern classification, in particular to a car model recognition method based on a two-class support vector machine and a genetic algorithm. Background technique [0002] Traffic information collection is the basis for building a dynamic traffic information platform for intelligent transportation systems, and vehicle types are an important part of traffic information. Road and bridge, parking lot charging system, road and bridge management and monitoring system, etc. all need vehicle type identification. In the intelligent traffic management system, the vehicle type recognition system can automatically and real-time detect passing vehicles and identify the vehicle type, license plate, and vehicle logo of the traffic management system, which can be widely used in road vehicle information records, expressway automatic toll collection, electronic police Monitoring, parking lot safety management, accident, s...
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IPC IPC(8): G06K9/66
Inventor顾晓清倪彤光薛磊
OwnerCHANGZHOU UNIV