ECOC (European Conference on Optical Communication) encoding classification method based on rejected random subspace

Abstract

The invention discloses an ECOC encoding classification method based on a rejected random subspace. The method comprises the steps as follows: 1), a shape feature of a classified target is encoded by ECOC, a group of codes are constructed for each to-be-classified target set, and a plurality of SVM (support vector machine) classifiers are constructed on each code bit through the rejected random subspace and an SVM; 2), an integrated classifier of the plurality of the SVM classifiers is constructed in each code bit with the ECOC encoding method, an external classification refusing mechanism is arranged outside the integrated classifier, a classification result of a basic classifier in the integrated classifier is subjected to decision fusion with a voting method, and if classified target of the code cannot be determined finally from the final result, the classification is refused through the external classification refusing mechanism; and a classification category is judged according to a detection sample and a Hamming distance and or an Euclidean distance of an encoding matrix. Experiments show that the design system can remarkably improve the reliability and the accuracy rate of vehicle type classification in a reasonable range of a classification refusing rate.

Description

technical field [0001] The invention belongs to the field of intelligent image analysis, and in particular relates to an ECOC code classification method based on a random subspace of recognition rejection. Background technique [0002] The vehicle type recognition system is an important part of the intelligent transportation system, and it is also a hot topic in the interdisciplinary research of computer vision, image processing and pattern recognition. Therefore, the research on related technologies in the field of vehicle type recognition is receiving widespread attention. In the field of pattern recognition in recent years, it is mainly to improve the classification accuracy as the standard of system performance. [0003] At present, the widely used car model recognition method is to use classifiers to distinguish various car models. The key to its success is firstly to describe the characteristics of various types of vehicle image sets, and secondly to select an appropri...

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Problems solved by technology

[0005] The object of the present invention is to provide an ECOC coding classification method based on a random subspace of rejection, which solves the problems of low reliability of automobile image classification in the prior art and serious consequences easily caused by wrong classification.

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