Unlicensed vehicle detection method based on adaboost and svm
A technology for unlicensed vehicles and detection methods, which is applied in the directions of instruments, character and pattern recognition, computer parts, etc., can solve the problems of increasing the false detection rate of the background difference method, unable to realize the detection of unlicensed vehicles, etc., and achieves shortened detection time, The effect of reducing false alarm probability and high generalization performance
Active Publication Date: 2016-11-02
沈阳聚德视频技术有限公司
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[0007] Due to the efficiency of the algorithm itself and the limitation of the DSP frame rate, the above three algorithms have certain limitations in practical applications. For example, the inter-frame difference method and the optical flow method are not suitable for occasions with low frame rates. The false detection rate of the time-background subtraction method increases significantly
[0008] In addition, the current vehicle detection algorithm based on single-frame image information relies too much on license plate information and template matching between license plates, and it is basically impossible to detect unlicensed vehicles
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[0053] The present invention will be further elaborated below in conjunction with the accompanying drawings of the description.
[0054] The present invention adopts the basic principle and framework of AdaBoos to detect faces in video sequences, and proposes an unlicensed vehicle detection method based on AdaBoost and Support Vector Machine (SVM) in video sequences
[0055] The AdaBoost detector is essentially a two-class classification of detection window images. The reason why it is successfully applied to target detection in video sequences is that this method uses integral images to quickly calculate Haar features, and then do cascaded binary tree classification, which can be used in a large number of In the candidate detection window of , the non-target samples are quickly judged.
[0056] The unlicensed vehicle detection method based on AdaBoost and SVM in the video sequence of the present invention is as Figure 4 shown, including the following steps:
[0057] 1) On ...
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The invention relates to an unlicensed vehicle detection method based on AdaBoost and SVM, comprising the following steps: 1) on a DSP platform, perform high-multiple downsampling on the row and column directions of the original video sequence image to obtain an RGB three-channel color image; 2 ) For the above-mentioned RGB three-channel color image, comprehensively consider the edge information and color information of the RGB three-channel color image, and synthesize a grayscale image; 3) For the above-mentioned synthetic grayscale image, use the AdaBoost detector to realize the detection of unlicensed vehicles in the video sequence; 4) Establish a nonlinear two-class SVM classifier for the detected target and background to further reduce the false alarm probability. The present invention can quickly determine non-target samples in a large number of candidate detection windows, and is successfully applied to target detection in video sequences, and the detection time is shortened by about 1 / 3.
Description
technical field [0001] The invention relates to an intelligent traffic detection technology, in particular to an unlicensed vehicle detection method based on AdaBoost and SVM. Background technique [0002] Intelligent Transportation System (ITS) started from the computerization of traffic management in the 1960s and 1970s. , Comprehensive transportation management system that plays a role in all directions. [0003] Vehicle detection in video sequences is an application of moving object detection in the field of intelligent transportation. Currently commonly used vehicle detection algorithms based on adjacent frame image information are: [0004] (1) Inter-frame difference method: This algorithm is to subtract the gray value of the corresponding pixel of the two frames of images before and after. If the gray value difference is small, it can be considered that there is no car passing by the point; otherwise, the gray value changes greatly, then Think a car is passing by. ...
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IPC IPC(8): G06K9/46
Inventor 陆振波董铁军付存伟于维双赵全邦
Owner 沈阳聚德视频技术有限公司