Transform edge detection

Aghagolzadeh, Sabzali; Ersoy, Okan K.

doi:10.1117/12.130262

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1994

1997

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Cited by 5 publications

(2 citation statements)

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“…Mintz [13] introduced another algorithm that is based on a cumulative voting scheme to declare a pixel to be an edge pixel. A transform-based edge detection algorithm was presented in [14]. It divides the image into blocks; performs a fast transformation, such as DCT; multiplies each block by a bandpass mask; then applies an inverse transformation to detect zero-crossings.…”

mentioning

confidence: 99%

A Real-Time Edge Detector: Algorithm and VLSI Architecture

Alzahrani

Chen

1997

Real-Time Imaging

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mentioning

confidence: 99%

A Real-Time Edge Detector: Algorithm and VLSI Architecture

Alzahrani

Chen

1997

Real-Time Imaging

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“…Medical images in general , cannot be classified by their intensity values or a sharp distinction of edges alone [1][2][3][4] . The methods that have been most useful for medical image segmentation problems have also considered the inclusion of image texture as a feature [5-61.…”

Section: Introductionmentioning

confidence: 99%

Application of genetic optimization to medical image segmentation

Cornely

Kuklinski

Proceedings of 1994 20th Annual Northeast Bioengineering Conference

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A number of important problems in medical imaging can be classified as segmentation problems. These segmentation problems can be formulated as configurational optimization problems by representing the configurations of interest in an image as unique subsets of the complete image. An effective segmentation optimization algorithm must determine the specific image subset that best exhibits an apriori set of quantative characteristics. In this paper a genetic optimization algorithm was used to produce a population of individual sub-images that were tested via. a quantitative objective function, ranked using a linear fitness and decrement scheme, and modified using a genetic crose-over operator. The algorithm was found to converge within twenty five to fifty generations to a good fit to the targeted configuration in a robust and efficient manner.

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On the discrete cosine transform computation

Britaňák

1994

Signal Processing

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Transform edge detection

Cited by 5 publications

References 12 publications

A Real-Time Edge Detector: Algorithm and VLSI Architecture

A Real-Time Edge Detector: Algorithm and VLSI Architecture

Application of genetic optimization to medical image segmentation

On the discrete cosine transform computation

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