A line detection and description algorithm based on swarm intelligence

Abstract

In this work, we use the principles of Swarm Intelligence to establish a novel algorithm for detecting and describing straight edges in images. The algorithm uses a set of individual mobile agents with limited cognitive possibilities. Using their memory and communication abilities, the agents can establish fast and robust solutions. The agents initially move randomly in a two dimensional space defined by an arbitrary input image or image sequence. In every time step, each agent calculates the derivative values in x and y direction at its current position and thresholds these values subsequently. If an agent discovers an edge or respectively a straight edge, it follows this straight edge and stores its start point. When it reaches the straight edge's end, it marks its last position as its stop point. As a kind of indirect communication between the agents, each of them leaves important information at each new position discovered. Thus each agent can benefit from the calculations any other agent has done before, which speeds up the algorithm. This new approach is a fast alternative to classical line finding operation like e.g. the Hough Transform.