Evolutionary Gabor Filter Optimization with Application to Vehicle Detection

Abstract—Despite the considerable amount of research work on the application of Gabor filters in pattern classification, their design and selection have been mostly done on a trial and error basis. Existing techniques are either only suitable for a small number of filters or less problem-oriented. A systematic and general evolutionary Gabor filter optimization (EGFO) approach that yields a more optimal, problem-specific, set of filters is proposed in this study. The EGFO approach unifies filter design with filter selection by integrating Genetic Algorithms (GAs) with an incremental clustering approach. Specifically, filter design is performed using GAs, a global optimization approach that encodes the parameters of the Gabor filters in a chromosome and uses genetic operators to optimize them. Filter selection is performed by grouping together filters having similar characteristics (i.e., similar parameters) using incremental clustering in the parameter space. Each group o...

• Type: Conference
• Year: 2003
• Where: ICDM
• Authors: Zehang Sun, George Bebis, Ronald Miller
• Keywords: Data Mining, Gabor filter Optimization, Gabor filters, ICDM 2003, Incremental Clustering