Abstract

Camera calibration is necessary in machine vision application field. Calibration model has nonlinear characteristics, and establishment of mathematical model is often a complicated process, but neural network can solve the complex nonlinear problem effectively, neural network has strong nonlinear approximation ability, adaptive network parameters and fast learning. This paper presents a neurocalibration approach about camera calibration based on back propagation (BP) neural network optimized by genetic algorithm (GA), GA can optimize net parameters about connection weights and threshold values. Making a comprehensive comparison between GA-BP neural network and BP neural network. The experimental results show that the GA-BP neurocalibration can be effective and feasible by this way.

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