Fundamental frequency Gabor filters for object recognition

Gabor filters are a widely used feature extraction method in image analysis. In this study, a method is presented that utilises Gabor filters for extracting fundamental frequencies of objects. The fundamental frequencies represent the shape of an object and can be used to classify objects with dissimilar spatial dimensions. Theoretical results are verified by experiments with real images of electronic components. Experiments indicate that the fundamental frequency Gabor filters are a robust tool for rotation and translation invariant object recognition.