Edge Detection in Range Images Using a Modified Canny Filter
Cheribet Mohamed, Smaine Mazouzi · 2019
Image segmentation is a crucial step in any image analysis process. It consists in preparing the image to make it more usable by an automatic process, such interpreting and understanding its content. In this paper, we introduce a novel method for range image segmentation. The proposed method proceeds by adapting the principle of the Canny filter, commonly utilized for greyscale and colour images, to be applied for range images, where depths in these images should be differently handled. Instead of using raw image data, a new image of angles between normal vectors according some given directions is computed and then used to compute a new gradient image. Canny steps are then applied on the latter image, producing precise and well located edges. Experimentation on real images from the ABW database shows that edges in range images are correctly detected.