Binocular vision obstacle detection system and method based on convolutional neural network

Abstract

The invention discloses a binocular vision obstacle detection system and a binocular vision obstacle detection method based on a convolutional neural network. The binocular vision obstacle detection system consists of an image acquisition module and an obstacle detection module. The image acquisition module acquires a binocular image and transmits the binocular image to the obstacle detection module to perform corresponding data processing on acquired image data, so as to obtain a precise obstacle region. The binocular vision obstacle detection method comprises the steps of: firstly, subjecting the acquired original image to median filtering processing; then correcting the binocular image according to camera parameters; designing a new convolution kernel to be used in a convolutional neural network structure for generating a precise disparity map; and finally, detecting the precise obstacle region in the image by adopting an improved V-parallax method. The binocular vision obstacle detection system and the binocular vision obstacle detection method have the advantage of being high in obstacle detection precision under conditions such as complicated light and small obstacles, and showing good robustness.

Description

technical field [0001] The present invention relates to the technical field of binocular vision image processing, in particular to a binocular vision obstacle detection system based on a convolutional neural network and a detection method thereof. Background technique [0002] With the advancement of computer technology, smart cars have developed rapidly and are widely used in fields such as national defense, scientific research and daily life. Among them, obstacle detection is the core issue in smart car navigation. [0003] The convolutional neural network is a feed-forward network whose artificial neurons can respond to the units within the coverage area, including convolutional layers and pooling layers, and has excellent performance in image processing. In recent years, it has received more and more attention from people, and its application fields have become more and more extensive. [0004] At present, the obstacle detection method based on binocular vision has gra...

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Problems solved by technology

[0006] In view of the above problems, the object of the present invention is to provide a binocular visual obstacle detection system and its detection method based on convolutional neural network, to solve the problem of obstacle detection accuracy and system robustness of the traditional binocular visual obstacle detection method. Deficiencies in other aspects

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