To realize automatically detecting and recording system of freight trains

it's necessary to detect whether the locks of freight trains exist by the image of freight trains when they are entering railway stations. An approach of fast lock detection is put forward

which is based on RBF neural network and improved genetic algorithm. In this method

firstly extract the projection features of images

linear moment features of edge images

and the features of gray histograms of images

and these features reflect different characters of targets from different points of view

and then they are normalized to the input vector of RBF neural network

and RBF neural network is used for detection and location. At the same time

improved genetic algorithm is used to search the whole image

and searching process is speeded up because the genetic algorithm is a parallel and robust algorithm. In addition

image preprocessing is not done alone

and gray variation of images is eliminated during the process of feature extraction. Experiment results show that the method can overcome the problems of many types

deformation

and the variation of environmental brightness

and have the fast speed and high success rate of detection

and can be put into practical application. Therefore

the method has significant engineering value.