Open AccessJournal Article
Fast Binary Dilation/Erosion Algorithm Using Kernel Subdivision
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TL;DR: The Kernel Sub-Division algorithm as discussed by the authors decomposes the n-dimensional structuring element, into several subsets and operates on the object contours in the image to reduce the complexity of binary morphological dilation and erosion.
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Abstract: Numerous algorithms have been proposed in the literature to speed up dilation/erosion operations. The motivation has been to reduce computational complexity by exploiting the structuring element and the image object properties. This paper presents a new algorithm for binary morphological dilation and erosion called the Kernel Sub-Division algorithm and discusses its implementation in the two dimensional case. It decomposes the n-dimensional structuring element, into several subsets and operates on the object contours in the image. The image characteristics are exploited by subdividing the object contours into bins while performing contour processing. The elegance of the algorithm lies in its retaining the correspondence to the output of the classical implementation with massive speed gain. The results of the algorithm on a statistically significant test set of images, showed that it performed five times better than the classical implementation for a 3x3 kernel. It also demonstrated a marginal rise in execution time with increasing size of the kernel.
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Citations
•Dissertation
Adéquation Algorithme Architecture et modèle de programmation pour l'implémentation d'algorithmes de traitement du signal et de l'image sur cluster multi-GPU
Vincent Boulos
- 18 Dec 2012
TL;DR: L’am´elioration notable du d´ebit sortant d’une applicationstreaming de calcul de carte de saillence visuelle a d´emontr´e l’efficacit´e de notre outil pourl’impl´ementation d”une solution sur cluster multi-GPU.
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References
Mapping global urban boundaries from the global artificial impervious area (GAIA) data
Delineating multi-scenario urban growth boundaries with a CA-based FLUS model and morphological method.
TL;DR: This paper argues that the delineation needs to integrate the top-down approach with CA for projecting complex land use changes under designed scenarios, and proposes a CA-based method called the future land use simulation (FLUS) that can support urban planning by generating feasible patterns for UGBs under different planning scenarios.
403
Recursive implementation of erosions and dilations along discrete lines at arbitrary angles
TL;DR: The algorithm is generalized to erosions and dilations along discrete lines at arbitrary angles and the padding problem is addressed; so that the operation can be performed in place without copying the pixels to and from an intermediate buffer.
154
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Baoshan Guo,Cheng Lei,Cheng Lei,Hirofumi Kobayashi,Takuro Ito,Yaxiaer Yalikun,Yiyue Jiang,Yo Tanaka,Yasuyuki Ozeki,Keisuke Goda,Keisuke Goda +10 more
TL;DR: High‐throughput label‐free single‐cell screening of lipid‐producing microalgal cells with optofluidic time‐stretch quantitative phase microscopy holds promise as an effective analytical tool for microalgae‐based biofuel production.
76
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TL;DR: The proposed algorithm performs ordered propagation using Euclidean distance transformation without generating any distance map, which allows optimization of both the time and memory demand.
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