Memory efficient vision based line feature extraction for tiny mobile robots

Abstract

This paper presents implementation of a memory efficient all integer line feature extraction algorithm for tiny autonomous mobile robot with limited on-chip memory. A circular buffer is used to bring image data from off chip to the on chip memory of the DSP for detecting edges. Afterwards a gradient based Hough transform is used to group collinear pixels which are processed to detect end points and length of the line segments. Approximation of the two dimensional Hough parameter space using a one dimensional array is discussed. Experimental results illustrate the performance of these features extraction on real and synthetic images. © 2009 Springer Berlin Heidelberg.