Effective Detection of Digital Bar Segments with Hough Transform

Abstract

This paper deals with the detection of generalized digital straight line segments, or digital bars, using Hough transform (HT). Straight line segments are classified according to the nature of the image space. Digital straight line segments, assumed to be those which can be obtained by grid-intersect quantization of ideal straight line segments, are generalized to represent bars of non-unitary width, and their mapping into a slope/intercept parameter space is characterized. The shortcomings of having discrete parameter space implied by most HTs are identified and two post-HT techniques (connectedness analysis and merging stage) to alleviate such shortcomings are discussed. A simple technique for connectedness analysis of the evidence produced by the HT, which can confirm the presence of straight features in the image and determine their respective endpoints, is described. The complete technique for detection of digital bars is exemplified for an actual image and its implementation in linear arrays of transputers is also discussed.