A new set of fast algorithms for mathematical morphology

Bleau, André; Guise, Jacques de; LeBlanc, A.R.

doi:10.1016/1049-9660(92)90038-5

Cited by 25 publications

(13 citation statements)

References 19 publications

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“…In rainfall based watersheds every path starts from pixel at higher altitude and end in a pixel at lowest altitude. A regional minimum is a pixel having gray level value smaller than any other pixels in the region [3,[8][9][10][11]. Hence, a steepest descending path SP (p,μ) can be defined as below, [2,13], and eventually reaches M.…”

Section: Definition 1: a Path " " Of Length L Between Two Pixels ' 'mentioning

confidence: 99%

An Improved Fast Watershed Algorithm based on finding the Shortest Paths with Breadth First Search

Suphalakshmi¹,

Anandhakumar²

2012

IJCA

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A watershed based on rainfall simulation is a proven technique for image segmentation. The only problem associated with it is the path regularization for pixels in the plateau. As the existing methods employ sequential techniques, the complexity of the algorithms remains high due to repetitive scanning of pixels. We propose an iterative method for finding the shortest and steepest path based on Breadth first search (BFS), which addresses the path regularization problem eliminating the repetitive scans. Experiments show, that the proposed algorithm significantly reduces the running time without compensating the performance when compared with the fastest known algorithm. General TermsFast watersheds, Image segmentation, Breadth First search, shortest path, path regularization. INTRODUCTIONImage segmentation is a fundamental problem in image analysis. The segmentation process can rely both on the uniformity of features within the regions or on edge evidence. Idea of watershed algorithm was developed from the field of topography. If we consider the analogy of a landscape and rain, water will find the swiftest descent path until it reaches some lake or sea, we can envisage lakes and seas correspond to regional minima [7]. The landscape can be completely partitioned into regions which draw water to a particular sea or lake. These regions are influence zones of the regional minima in an image which forms catchment basin. Though there are lot of variations and combinations with other methods, watershed still remain in research to improve either its time complexity, reducing the problem of over segmentation, and solving the path regularization. We, in this paper address all the three problems of watershed with our proposed algorithm.

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Section: Definition 1: a Path " " Of Length L Between Two Pixels ' 'mentioning

confidence: 99%

An Improved Fast Watershed Algorithm based on finding the Shortest Paths with Breadth First Search

Suphalakshmi¹,

Anandhakumar²

2012

IJCA

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“…Identical results are achieved by identifying all pixels whose blackness is above u, then using their image locations as seed points for region growing operations which are allowed to extend beyond this initial coordinate set, but not into regions marked as below l. Regions above u and below l may be identified by simple thresholding, The required region growing may be achieved via a variant of the familiar morphological dilation operator which is both idempotent and employs initial and transformable sets (Appendix 1 and [14]). …”

Section: Thresholding With Hysteresis Using Mathematical Morphologymentioning

confidence: 99%

“…A morphological operation is said to be idempotent if its subsequent application produces no further change in the image. Efficient algorithms implementing idempotent dilation (and other morphological operations) with initial and transformable sets are available [14]. If B is the input grey level image and I, T , O are binary images, the above algorithm may be implemented as follows:…”

Section: Thresholding With Hysteresis Using Mathematical Morphologymentioning

confidence: 99%

Thresholding Images of Line Drawings with Hysteresis

Pridmore

2002

Lecture Notes in Computer Science

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Abstract. John Canny's two-level thresholding with hysteresis is now a de facto standard in edge detection. The method consistently outperforms single threshold techniques and is simple to use, but relies on edge detection operators' ability to produce thin input data. To date, thresholding with hysteresis has only been applicable to thick data such as line drawings by top-down systems using a priori knowledge of image content to specify the pixel tracks to be considered. We present, and discuss within the context of line drawing interpretation, a morphological implementation of thresholding with hysteresis that requires only simple thresholding and idempotent dilation and which is applicable to thick data. Initial experiments with the technique are described. A more complete evaluation and formal comparison of the performance of the proposed algorithm with alternative line drawing binarisation methods is underway and will be the subject of a future report.

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“…One advantage of this approach is that no new intensity extrema (or corresponding watershed regions) are created as scale is increased. In spite of recent speed improvements [5], [14] the mathematical morphology scalespace approach remains computationally demanding.…”

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confidence: 99%

Image segmentation and analysis via multiscale gradient watershed hierarchies

Gauch

1999

IEEE Trans. on Image Process.

249

108

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Abstract-Multiscale image analysis has been used successfully in a number of applications to classify image features according to their relative scales. As a consequence, much has been learned about the scale-space behavior of intensity extrema, edges, intensity ridges, and grey-level blobs. In this paper, we investigate the multiscale behavior of gradient watershed regions. These regions are defined in terms of the gradient properties of the gradient magnitude of the original image. Boundaries of gradient watershed regions correspond to the edges of objects in an image. Multiscale analysis of intensity minima in the gradient magnitude image provides a mechanism for imposing a scale-based hierarchy on the watersheds associated with these minima. This hierarchy can be used to label watershed boundaries according to their scale. This provides valuable insight into the multiscale properties of edges in an image without following these curves through scale-space. In addition, the gradient watershed region hierarchy can be used for automatic or interactive image segmentation. By selecting subtrees of the region hierarchy, visually sensible objects in an image can be easily constructed.Index Terms-Image segmentation, multiscale image analysis, watershed regions.

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A new set of fast algorithms for mathematical morphology

Cited by 25 publications

References 19 publications

An Improved Fast Watershed Algorithm based on finding the Shortest Paths with Breadth First Search

An Improved Fast Watershed Algorithm based on finding the Shortest Paths with Breadth First Search

Thresholding Images of Line Drawings with Hysteresis

Image segmentation and analysis via multiscale gradient watershed hierarchies

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