A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of the Hough transform
Computer Vision, Graphics, and Image Processing
Hough transform for line recognition complexity of evidence accumulation and cluster detection
Computer Vision, Graphics, and Image Processing
Effective exploitation of a zero overhead loop buffer
Proceedings of the ACM SIGPLAN 1999 workshop on Languages, compilers, and tools for embedded systems
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
Feasibility analysis of ultra high frame rate visual servoing on FPGA and SIMD processor
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
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In the first part of this paper, an improved slope-intercept like representation is proposed for implementation of Standard Hough Transform (SHT) on SIMD (Single-Instruction, Multiple-Data) architectures with no local indirect addressing support. The real-time implementation is realized with high accuracy on our Wireless Smart Camera (WiCa) platform. The processing time of this approach is independent of the number of edge points or the number of detected lines. In the second part, we focus on analyzing the differences between the SHT implementations on 1-D SIMD architectures with and without local indirect addressing. Three aspects are compared: total operation number, memory access/energy consumption, and memory area cost. When local indirect addressing is supported, the results show a considerable amount of reduction in total operations and energy consumption at the cost of extra chip area. The results also show that the focuses for further optimization of these two architectures are different.