Detection of target models in 2D images by line-based matching and a genetic algorithm

In this paper we propose an algorithm to detect a 2D target model in cluttered environments and to find its scale s, translation (t_x, t_y) and orientation θ. The algorithm first extracts straight line segments from the image. Next, generating transformation vectors (s, t_x, t_y, θ), the algorithm computes the fitness values for these vectors through matching between data line segments extracted from the image and model line segments transformed by (s, t_x, t_y, θ). And, by a generic algorithm, the algorithm searches for a transformation vector with the highest fitness value. The obtained transformation vector gives the scale, translation and orientation of the model in the image.