Abstract
The Hough transform is an efficient method for extracting lines in images. Precision of detection relies on how to find and locate accurately the peak in Hough space after the voting process. In this paper, a statistical method is proposed to improve peak localization by considering quantization error and image noise, and by considering the coordinate origin selection. The proposed peak localization is based on butterfly analysis: statistical standard variances and statistical means are computed and used as parameters of fitting and interpolation processes. We show that accurate peak parameters are achieved. Experimental results compare our results with those provided by other peak detection methods. In summary, we show that the proposed peak localization method for the Hough transform is both accurate and robust in the presence of quantization error and image noise.
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Xu, Z., Shin, BS. (2014). A Statistical Method for Peak Localization in Hough Space by Analysing Butterflies. In: Klette, R., Rivera, M., Satoh, S. (eds) Image and Video Technology. PSIVT 2013. Lecture Notes in Computer Science, vol 8333. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53842-1_10
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DOI: https://doi.org/10.1007/978-3-642-53842-1_10
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