Flooding-based watershed algorithm and its prototype hardware architecture

Rambabu, C.; Chakrabarti, Indrajit; Mahanta, Anil

doi:10.1049/ip-vis:20040397

Cited by 22 publications

(21 citation statements)

References 24 publications

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“…It leads to a consequent loss in performance. The present paper describes a hillclimbing based technique which overcomes the drawback of the flooding-based algorithm [26]. The proposed hillclimbing technique is also faster than the flooding method [26].…”

Section: Introductionmentioning

confidence: 99%

“…Recently, an improved technique of simulated flooding based watershed algorithm [26] has been proposed. Involving only one single queue, it exhibits equivalent performance at reduced hardware complexity while compared to Meyer's algorithm [12].…”

Section: Introductionmentioning

confidence: 99%

“…Involving only one single queue, it exhibits equivalent performance at reduced hardware complexity while compared to Meyer's algorithm [12]. However, the flooding based algorithm [26] suffers from an important drawback in that no synchronization in label propagation is possible in a non-minimum plateau which has more than one closely located regional minima. It leads to a consequent loss in performance.…”

Section: Introductionmentioning

confidence: 99%

“…The present paper describes a hillclimbing based technique which overcomes the drawback of the flooding-based algorithm [26]. The proposed hillclimbing technique is also faster than the flooding method [26]. For, introducing a steepest lower complete image in the hillclimbing algorithm reduces the number of searching points, whereas the label propagation in the flooding-based method [26] involves a depth-first search mechanism, processing one local minimum at time.…”

Section: Introductionmentioning

confidence: 99%

“…The proposed hillclimbing technique is also faster than the flooding method [26]. For, introducing a steepest lower complete image in the hillclimbing algorithm reduces the number of searching points, whereas the label propagation in the flooding-based method [26] involves a depth-first search mechanism, processing one local minimum at time. Moreover, the proposed method has a reduced time complexity as it does away with inherently time-consuming lower complete transformation normally involved in a conventional hillclimbing method [14,24].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

An Efficient Hillclimbing-based Watershed Algorithm and its Prototype Hardware Architecture

Rambabu

Chakrabarti

2008

J Sign Process Syst Sign Image Video Technol

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Image segmentation is the process of isolating objects in an input image, that is, partitioning the image into disjoint regions, such that each region is homogeneous with respect to some property, such as gray value or texture. Watershed-based image segmentation has gained much popularity in the field of biomedical image processing and computer vision where large images are not uncommon. Time-critical applications like road traffic monitoring, and steel fissure analysis require fast realization of the segmentation results. The present paper proposes a fast watershed transform based on hillclimbing technique. The complexity of the algorithm has been reduced by doing away with multiplication normally required to form a lower complete image in an intermediate step of the overall segmentation. The reduced complexity makes the algorithm suitable for dedicated hardware implementation. An FPGA-based architecture has been developed to implement the proposed algorithm involving moderate hardware complexity. This architecture enhances the applicability of this algorithm for real-time applications.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

An Efficient Hillclimbing-based Watershed Algorithm and its Prototype Hardware Architecture

Rambabu

Chakrabarti

2008

J Sign Process Syst Sign Image Video Technol

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Real-time image segmentation based on a parallel and pipelined watershed algorithm

Trieu

Matsumoto

2007

J Real-Time Image Proc

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The watershed transformation is a popular image segmentation technique for gray scale images. This paper describes a real-time image segmentation based on a parallel and pipelined watershed algorithm which is designed for hardware implementation. In our algorithm:(1) pixels in a given image are repeatedly scanned from top-left to bottom-right, and then from bottom-right to topleft, in order to achieve high performance on a pipelined circuit by simplifying memory access sequences, (2) all steps in the algorithm are executed at the same time in the pipelined circuit, (3) the amount of data that are scanned is gradually reduced as the calculation progresses by memorizing which data are modified in the previous scan, and (4) N pixels can be processed in parallel. In our current implementation on an off-the-shelf field-programmable gate array board, up to four pixels can be processed in parallel. The performance for 512 9 512 pixel images is fast enough to be the first step in real-time applications.

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Collective Neurodynamic Optimization for Image Segmentation by Binary Model with Constraints

Huang

2020

Cogn Comput

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Flooding-based watershed algorithm and its prototype hardware architecture

Cited by 22 publications

References 24 publications

An Efficient Hillclimbing-based Watershed Algorithm and its Prototype Hardware Architecture

An Efficient Hillclimbing-based Watershed Algorithm and its Prototype Hardware Architecture

Real-time image segmentation based on a parallel and pipelined watershed algorithm

Collective Neurodynamic Optimization for Image Segmentation by Binary Model with Constraints

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