Squat detection in railway rails using Gabor filter bank, SVM classifier and Genetic Algorithms

摘要

The paper presents an algorithm allowing for automatic detection of squat flaws in railway rails. These flaws can pose a threat to the safety of railway traffic. A Gabor filter bank along with SVM classifier were used in the detection process. The optimal number of features used to discriminate between squat and the area without squat as well as the parameters for classifier were selected with the help of Genetic Algorithm. Overall classification rate for the system was 95%.