Line recognition

The use of edge detection and localizing filters for the recognition of lines (narrow contrasting strips) in visual scenes is shown to produce systematic errors while being suboptimum with respect to noise. The authors derive optimum filters for the detection and localization of lines based on matched filtering in the line normal direction and a Wiener filter in the direction tangential to the line. The matched filters for the detection and localization of line normals in white noise have the form of the system response and its first derivative, respectively. The orthogonal least-restrictive Wiener filter is also closely approximated by the form of the system response in cased where Gaussian response and white noise dominate. Close approximations to the optimum filters for line recognition under these common conditions are readily realized. Line filters were integrated with the Boie-Cox edge detector. Results for images with mixed lines and edges show that the integrated Boie-Cox system is free of the systematic errors common to other edge recognition systems