Polarization characteristic multi-scale pooling classification algorithm for complex vehicle road environment

A classification algorithm and multi-scale technology, applied in computing, computer components, instruments, etc., to achieve good classification and recognition effects and improve the effect of semantic classification and recognition

Pending Publication Date: 2021-03-30
CHANGAN UNIV
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Problems solved by technology

[0005] In order to solve the technical problems existing in the prior art, the purpose of the present invention is to provide a polarization feature multi-scal

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  • Polarization characteristic multi-scale pooling classification algorithm for complex vehicle road environment
  • Polarization characteristic multi-scale pooling classification algorithm for complex vehicle road environment
  • Polarization characteristic multi-scale pooling classification algorithm for complex vehicle road environment

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[0032] The present invention will be described in detail below with reference to the accompanying drawings and examples.

[0033] See figure 1 The present invention passes the analysis of the vehicle environment medium information, and proposes to enhance the complex environment target imaging using polarization imaging, improve the imaging quality of the image acquired based on the turbid scattering medium; in turn design the polarization imaging scheme and builds a three-way imaging system to obtain polarization Image characteristics; finally proposed a multi-scale poolization algorithm based on polarization feature, a plurality of different detail features of the polarized image, improve the semantic segmentation effect and classification recognition ability of complex scenes by multi-scale poolization operation.

[0034] See figure 2 The Stokes vector of polarization information is expressed, wherein the parameter V is small in practical applications, almost negligible, and ...

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Abstract

The invention provides a polarization characteristic multi-scale pooling classification algorithm for a complex vehicle road environment, and classification of image targets in the complex vehicle road environment is realized. Firstly, vehicle road environment medium conditions are analyzed, and a high-quality imaging mode in a complex vehicle road environment is explored; secondly, a polarizationimaging scheme is designed based on a simulation experiment result, and a three-channel imaging system is assembled and calibrated. finally, a multi-scale pooling deep semantic recognition algorithmis proposed to realize recognition and classification of vehicle and road environment targets. Experimental results show that the semantic classification recognition effect of a complex scene can be effectively improved, and reliable technical guarantee is provided for safe auxiliary driving visual perception of vehicles in a complex vehicle road environment.

Description

Technical field [0001] The present invention relates to a polarization feature multi-scale cellularization classification algorithm for complex car environments, and specifically, a polarization imaging method and a depth learning semantic segmentation algorithm. Background technique [0002] At present, the main study of traffic environment awareness is divided into image target detection algorithm and image segmentation algorithm, in which target segmentation in the road image is one of the most basic and important research fields, and the target segmentation algorithm is mainly divided into traditional machine learning. Method and depth learning algorithm based on convolutional neural network. [0003] Traditional image segmentation algorithms are mainly divided into threshold segmentation, cluster segmentation, regional growth, and the like. Kaptur et al. Proposes the optimal entropy threshold method, for the image that cannot present the ideal double peak histogram, this met...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04
CPCG06V20/588G06N3/045G06F18/214G06F18/241G06F18/253Y02T10/40
Inventor 王会峰黄鹤关丽敏高荣温立民刘盼芝张佳佳王晓艳赵丹
Owner CHANGAN UNIV
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