The paper implements the improved HMAX model for vehicle type (make and model) recognition. The main improvement of this algorithm is using ITTI model with the characteristic of quick response to color, intensity or orientation discrimination, to select the saliency area. By this way the template can be more representative and more beneficial to the detection rate. In addition, the calculating of the variance of response degree between different images and the same template eliminates redundant

more »

... templates, which make contribution to reducing the time of classification. Analyzing and experiments claims that the improved HMAX model can be effective and reliable by the detection rate at 95%, with enough features extracted, 5% -10% higher than current vehicle type recognition methods and 1% -2% higher than original HMAX model. In addition, with the template screening method added, the improved HMAX model can keep the detection rate and curtail the classification time by quarter time. According to the optimal setting by the final value estimation, the detection rate is about 92%, and the classification time is 0.6 s/image, with promotion to the past.