A Hardware Implementation for Colour Edge Detection Using Prewitt-Inspired Filters Based on Geometric Algebra

Orouji, Niloofar; Sadr, Ali

doi:10.1007/s00006-019-0941-8

Cited by 3 publications

(3 citation statements)

References 18 publications

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“…A hardware implementation for color edge detection using Prewittinspired filters based on geometric algebra is considered in [156]. Motivation comes from geometric algebra (GA) as a powerful mathematical tool that offers intuitive solutions for image-processing problems, including color edge detection.…”

Section: Image and Color Image Processingmentioning

confidence: 99%

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New Applications of Clifford’s Geometric Algebra

Breuils

Tachibana

Hitzer

2022

Adv. Appl. Clifford Algebras

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The new applications of Clifford's geometric algebra surveyed in this paper include kinematics and robotics, computer graphics and animation, neural networks and pattern recognition, signal and image processing, applications of versors and orthogonal transformations, spinors and matrices, applied geometric calculus, physics, geometric algebra software and implementations, applications to discrete mathematics and topology, geometry and geographic information systems, encryption, and the representation of higher order curves and surfaces.

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Section: Image and Color Image Processingmentioning

confidence: 99%

“…So far, all color edge detection hardwares in any GA framework exploited RBS filters. Nevertheless, [156] presents a full-hardware architecture for efficient execution of PIS filters. Importantly, PIS filters consume less computational resources and are faster to execute.…”

Section: Image and Color Image Processingmentioning

confidence: 99%

New Applications of Clifford’s Geometric Algebra

Breuils

Tachibana

Hitzer

2022

Adv. Appl. Clifford Algebras

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show abstract

“…So far, all color edge detection hardwares in GA have exploited RBS filters. The paper of Orouji and Sadr 206 presents a full‐hardware architecture for efficient execution of PIS filters, consuming less computational resources and being faster to execute, for example, at the same speed the Gaalop pre‐compiler uses twice as much resources as the proposed hardware. The latter is able to execute the edge detection algorithm almost 315 times faster than a GA co‐processor, with only 2.5 times of its resources.…”

Section: Signal Image and Video Processingmentioning

confidence: 99%