Implementation of the Hough transform (HT) for line detection requires massive computation, large memory space and high bandwidth. Without parallel processing on a proper platform, it can be hardly implemented in real-time, especially with high accuracy on high-resolution images. This paper proposes several efficient methods for implementation of HT on SIMD (single-instruction, multiple-data) architecture. All lines in an image/frame can be detected in real time with the proposed voting method, the novel Hough space (HS) structures, and the efficient image ldquorotationrdquo mechanism. With suggested refinement and tracking approach, we can capture and follow the target lines with very high accuracy. Analysis and comparison are elaborated with real-time implementation on our wireless smart camera (WiCa) platform, which is a powerful image/video processing platform developed by NXP Semiconductors. Moreover, two different applications, lane detection and gesture control, are also developed on this platform.
['Yifan He', 'Zoran Zivkovic', 'Richard P. Kleihorst', 'Alexander Danilin', 'Henk Corporaal']
Real-time implementations of Hough Transform on SIMD architecture