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Target identification method based on training Adaboost and support vector machine

A technology of support vector machine and self-adaptive enhancement, applied in the field of image recognition, it can solve the problem of incorrect image processing, etc., and achieve high precision and high efficiency.

Inactive Publication Date: 2011-08-10
SHANGHAI JIAO TONG UNIV
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  • Summary
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AI Technical Summary

Problems solved by technology

However, the method of Y.T.Chen et al. only optimized the filtering speed of the wrong pictures encountered in the recognition process, but did not implement further processing for the acquisition of correct pictures

Method used

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  • Target identification method based on training Adaboost and support vector machine
  • Target identification method based on training Adaboost and support vector machine
  • Target identification method based on training Adaboost and support vector machine

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Embodiment Construction

[0035] The embodiments of the present invention are described in detail below. This embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operating procedures are provided, but the protection scope of the present invention is not limited to the following implementation example.

[0036] Such as figure 1 , 2 As shown, the specific implementation details of this example are as follows:

[0037] (1). Determine the number of stages of the Adaboost classifier and the technical index of each level according to the technical indicators: in this example, there are 12 levels of Adaboost classifiers in total, and the detection rate of each level of Adaboost classifier is set to 99.5%, and the false detection rate is 99.5%. 50%. The detection rate of the SVM classifier to reject the separation plane and skip the separation plane was set at 99.5%.

[0038] (2).Using the UIUC car data set as the sam...

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Abstract

The invention relates to a target identification method based on training Adaboost and a support vector machine, relating to the technical field of image processing. The target identification method comprises the following steps: extracting haar characteristics of an original sample and using the haar characteristics for training to obtain a cascading classifier based on the Adaboost and the SVM (support vector machine) and then carrying out target identification on an image to be identified by using the cascading classifier to obtain a final identification result. The target identification method can accurately and rapidly identify targets such as people, vehicles and the like.

Description

technical field [0001] The invention relates to a method in the technical field of image recognition, in particular to a target recognition method based on training adaptive enhancement (Adaboost) and support vector machine (SVM). Background technique [0002] The research and application of object recognition methods is an active branch in the field of computer vision and intelligent video analysis, and plays an important role in video surveillance, security inspection, automatic control and other systems. In a complex environment, efficient and accurate identification of targets will provide a solid and effective guarantee for subsequent processing links such as target tracking and behavior analysis. [0003] The current target recognition technology based on supervised learning usually designs classifiers with complex structures in order to achieve a high recognition rate. Results and data available in real time. As one of the difficulties of pattern recognition, effici...

Claims

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Application Information

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IPC IPC(8): G06K9/62
Inventor 宋利徐振超薛耿剑
Owner SHANGHAI JIAO TONG UNIV
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