Real Time Detection of Object Blob Localization Application using 1-D Connected Pixel and Windowing Method on FPGA

Autor:	CheeYuen Lam, R. A. A. Raof, Phaklen Ehkan, Suwimol Jungjit
Rok vydání:	2021
Předmět:	History Pixel business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Computer vision Artificial intelligence business Object (computer science) Field-programmable gate array Computer Science Applications Education
Zdroj:	Journal of Physics: Conference Series. 1755:012054
ISSN:	1742-6596 1742-6588
DOI:	10.1088/1742-6596/1755/1/012054
Popis:	Blob detection and localization is a common process used in the machine vision. Current existing blob detection method is using 2-dimensional kernel matrix which is higher in time consumption and also memory space. This study has proposed a dedicated digital architecture consist of two modules to detect binary image blob using only 1 -dimensional image pixel. First module is used to detect connected pixel in a row of pixel, and second module is used to perform windowing to justify blob location. This study has been successfully implemented and tested on Altera DE2 FPGA board. The proposed architecture only takes 24 clock cycles to deliver blob location and related features. The tested architecture only utilizes 1597 logic element, or 4.81% of the FPGA total resources.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a8d87b2f984a639573039f39fbf8665b https://doi.org/10.1088/1742-6596/1755/1/012054 Zobrazit plný text záznamu