Stereovision system of mobile robot: image pre-processing stage
Digital image processing merges with the field of artificial intelligence in the task of computer vision. This article continues the description of the pattern recognition system based on stereo vision technology. In a number of tasks related to machine vision, images in binary representation are used as input. Moreover, these tasks can be quite simple (outlining based on the color correlation of pixels), as well as complex (recognition and classification, positioning and autonomous navigation). The best results in pattern recognition are obtained using convolutional neural networks (CNN). However, the stage of preliminary image processing, which will be discussed in this article, plays an important role in achieving high quality recognition. In addition, binary image processing methods are applicable in the processing and analysis of grayscale and color images. This work is an integral part of the description of the stereovision system of a mobile robot, the neural network module of which has already been considered previously. The article presents the results of the pre-processing and filtering unit. Possible generalizations of the proposed approach based on quantum soft computing technology and quantum deep machine learning using quantum neural networks are discussed.