2012
DOI: 10.1007/s11554-012-0248-7
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GPU implementation of linear morphological openings with arbitrary angle

Abstract: Linear morphological openings and closings are important non-linear operators from mathematical morphology. In practical applications, many different orientations of digital line segments must typically be considered. In this paper, we (1) review efficient sequential as well as parallel algorithms for the computation of linear openings and closings, (2) compare the performance of CPU implementations of four state-of-the-art algorithms, (3) describe GPU implementations of two recent efficient algorithms allowin… Show more

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Cited by 14 publications
(7 citation statements)
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References 26 publications
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“…Along with the repeatability and lack of manual intervention this gives the new method a significant advantage, however, this was achieved using robust parameters, specifically; S h ¼ 10 , S L ¼ 2 pixels and L max ¼ 91. Application specific optimisations could reduce measurement time further, as could more efficient GPU implementations of morphological operators [36], that were outside the scope of this study.…”
Section: Resultsmentioning
confidence: 99%
“…Along with the repeatability and lack of manual intervention this gives the new method a significant advantage, however, this was achieved using robust parameters, specifically; S h ¼ 10 , S L ¼ 2 pixels and L max ¼ 91. Application specific optimisations could reduce measurement time further, as could more efficient GPU implementations of morphological operators [36], that were outside the scope of this study.…”
Section: Resultsmentioning
confidence: 99%
“…Additionally, it would be interesting to try adapting the stack-based algorithm to robust [4] and incomplete [8] path openings, or other schemes for making path openings more robust to noise. Di erent schemes for parallelization could also be explored (for example by dividing the grey levels, rather than pixels, among di erent processors), as well as e cient GPU implementations as has been explored in the 1D case [10].…”
Section: Discussionmentioning
confidence: 99%
“…However, it uses a histogram, consequently the whole signal to be processed must be known in advance, and the pixel values are limited to 8-bits. Instead, we propose using another fast algorithm [33], [34], which offers the following additional advantages: (i) it computes the output signal progressively, each time a pixel is added to a path; (ii) it can handle the signal borders in two different ways, by padding with −∞ V or with ∞ V ; (iii) it can handle any input data accuracy (integer or floating point) with no extra cost; (iv) the complexity is independent of the size of the opening; (v) it is fast and GPU compliant, as shown by Karas et al [35].…”
Section: B Path Filtering: Efficient Algorithmmentioning
confidence: 99%