SIFT-based object recognition for tracking in infrared imaging system

In this paper, we propose an automatic object tracking and recognition in unknown environments by using scale-invariant feature transform (SIFT) in PowerPC-based infrared (IR) imaging system. Proposed method consists of two stages. First, we must localize the interest point in position and scale of moving objects. Second, we must build a description of the interest point and recognize moving objects. Proposed SIFT method for an effective feature extraction in PowerPC-based IR imaging system consists of scale space, extrema detection, orientation assignment, key point description, and feature matching. SIFT descriptor sets up extensive range about 1.5 times than visual image when feature value of SIFT in IR image is less than visual image. Based on experimental results, the proposed method is extracted object's feature values in our system, and the result is presented by experiment.