Color line detection

Abstract

Color line extraction is an important part of the segmentation process. The proposed method is the generalization of the Gradient Line Detector (GLD) to color images. The method relies on the computation of a color gradient field. Existing color gradient are not "oriented": the gradient vector direction is defined up to π, and not up to 2π as it is for a grey-level image. An oriented color gradient which makes use of an ordering of colors is proposed. Although this ordering is arbitrary, the color gradient orientation changes from one to the other side of a line; this change is captured by the GLD. The oriented color gradient is derived from a generalization from scalar to vector: the components of the gradient are defined as a "signed" distance between weighted average colors, the sign being related to their respective order. An efficient averaging method inspired by the Gaussian gradient brings a scale parameter to the line detector. For the distance, the simplest choice is the Euclidean distance, but the best choice depends on the application. As for any feature extraction process, a post-processing is necessary: local maxima should be extracted and linked into curvilinear segments. Some preliminary results using the Euclidean distance are shown on a few images. © 2011 Springer-Verlag.