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Chung Ta King

dblp:61/3954 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1995
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Hardware accelerators and domain-specific architectures · 50% Parallel and multicore computing · 50%
Computer graphics and multimedia
1 paper
Image and video processing · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Parallel and multicore computing › parallel algorithms
parallel image processing
0.011995
Pipeline architectures for recursive morphological operations · IEEE Trans. Image Process. 1995
Hardware accelerators and domain-specific architectures
systolic array
0.011995
Pipeline architectures for recursive morphological operations · IEEE Trans. Image Process. 1995
Image and video processing
mathematical morphology
0.011995
Pipeline architectures for recursive morphological operations · IEEE Trans. Image Process. 1995

Methods — techniques the papers use, named apart from their topics

pipeline architecture · 0.0distributed-memory multicomputer · 0.0
YearPublicationVenuePosition
1995 Pipeline architectures for recursive morphological operations
abstract
Introduces efficient pipeline architectures for the recursive morphological operations. The standard morphological operation is applied directly on the original input image and produces an output image. The order of image scanning in which the operator is applied to the input pixels is irrelevant. However, the intent of the recursive morphological operations is to feed back the output at the current scanning pixel to overwrite its corresponding input pixel to be considered into computation at the following scanning pixels. The resultant output image by recursive morphology inherently depends on the image scanning sequence. Two pipelined implementations of the recursive morphological operations are presented. The design of an application-specific systolic array is first introduced. The systolic array uses 3 n cells to process an nxn image in 6 n-2 cycles. The cell utilization rate is 100%. Second, a parallel program implementing the recursive morphological operations and running on distributed-memory multicomputers is described. Performance of the program can be finely tuned by choosing appropriate partition parameters.
Frank Y. Shih, Chung Ta King, Christopher C. Pu
IEEE Trans. Image Process.2