Detailed Information

Cited 16 time in webofscience Cited 17 time in scopus
Metadata Downloads

Design of an Edge-Detection CMOS Image Sensor with Built-in Mask Circuits

Full metadata record
DC Field Value Language
dc.contributor.authorJin, Minhyun-
dc.contributor.authorNoh, Hyeonseob-
dc.contributor.authorSong, Minkyu-
dc.contributor.authorKim, Soo Youn-
dc.date.accessioned2023-04-27T22:40:50Z-
dc.date.available2023-04-27T22:40:50Z-
dc.date.issued2020-07-
dc.identifier.issn1424-8220-
dc.identifier.issn1424-3210-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/6465-
dc.description.abstractIn this paper, we propose a complementary metal-oxide-semiconductor (CMOS) image sensor (CIS) that has built-in mask circuits to selectively capture either edge-detection images or normal 8-bit images for low-power computer vision applications. To detect the edges of images in the CIS, neighboring column data are compared in in-column memories after column-parallel analog-to-digital conversion with the proposed mask. The proposed built-in mask circuits are implemented in the CIS without a complex image signal processer to obtain edge images with high speed and low power consumption. According to the measurement results, edge images were successfully obtained with a maximum frame rate of 60 fps. A prototype sensor with 1920 x 1440 resolution was fabricated with a 90-nm 1-poly 5-metal CIS process. The area of the 4-shared 4T-active pixel sensor was 1.4 x 1.4 mu m(2), and the chip size was 5.15 x 5.15 mm(2). The total power consumption was 9.4 mW at 60 fps with supply voltages of 3.3 V (analog), 2.8 V (pixel), and 1.2 V (digital).-
dc.format.extent12-
dc.language영어-
dc.language.isoENG-
dc.publisherMDPI-
dc.titleDesign of an Edge-Detection CMOS Image Sensor with Built-in Mask Circuits-
dc.typeArticle-
dc.publisher.location스위스-
dc.identifier.doi10.3390/s20133649-
dc.identifier.scopusid2-s2.0-85087104931-
dc.identifier.wosid000553143900001-
dc.identifier.bibliographicCitationSENSORS, v.20, no.13, pp 1 - 12-
dc.citation.titleSENSORS-
dc.citation.volume20-
dc.citation.number13-
dc.citation.startPage1-
dc.citation.endPage12-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaChemistry-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaInstruments & Instrumentation-
dc.relation.journalWebOfScienceCategoryChemistry, Analytical-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryInstruments & Instrumentation-
dc.subject.keywordPlusDB DYNAMIC-RANGE-
dc.subject.keywordPlusGLOBAL SHUTTER-
dc.subject.keywordPlusNOISE-
dc.subject.keywordPlusVISION-
dc.subject.keywordAuthorCMOS image sensor-
dc.subject.keywordAuthorcomputer vision-
dc.subject.keywordAuthoredge detection-
dc.subject.keywordAuthorlow power consumption-
dc.subject.keywordAuthorsingle-slope ADC-
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Advanced Convergence Engineering > Division of System Semiconductor > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kim, Soo Youn photo

Kim, Soo Youn
College of Advanced Convergence Engineering (Division of System Semiconductor)
Read more

Altmetrics

Total Views & Downloads

BROWSE