Enhanced autofocus algorithm using robust focus measure and fuzzy reasoning

Sang Yong Lee; Yogendera Kumar; Ji Man Cho; Sang Won Lee; Soo Won Kim

doi:10.1109/TCSVT.2008.924105

Enhanced autofocus algorithm using robust focus measure and fuzzy reasoning

Sang Yong Lee, Yogendera Kumar, Ji Man Cho, Sang Won Lee, Soo Won Kim

* Honorary professors

Research output: Contribution to journal › Article › peer-review

96 Citations (Scopus)

Abstract

A new passive autofocus algorithm consisting of a robust focus measure for object detection and fuzzy reasoning for target selection is presented. The proposed algorithm first detects objects distributed in the image using a mid-frequency discrete cosine transform focus measure and then selects the target object through fuzzy reasoning with three fuzzy membership functions. The proposed algorithm is designed as full digital blocks and fabricated using 0.35-μm CMOS technology. Experimental results obtained from various samples show that the present method is insensitive to Gaussian and impulsive noises and able to improve the quality of the image by focusing to the appropriate target object.

Original language	English
Article number	4498431
Pages (from-to)	1237-1246
Number of pages	10
Journal	IEEE Transactions on Circuits and Systems for Video Technology
Volume	18
Issue number	9
DOIs	https://doi.org/10.1109/TCSVT.2008.924105
Publication status	Published - 2008 Sep

Keywords

Autofocus (AF)
Focus measure
Fuzzy reasoning
Object detection

ASJC Scopus subject areas

Media Technology
Electrical and Electronic Engineering

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10.1109/TCSVT.2008.924105

Cite this

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title = "Enhanced autofocus algorithm using robust focus measure and fuzzy reasoning",

abstract = "A new passive autofocus algorithm consisting of a robust focus measure for object detection and fuzzy reasoning for target selection is presented. The proposed algorithm first detects objects distributed in the image using a mid-frequency discrete cosine transform focus measure and then selects the target object through fuzzy reasoning with three fuzzy membership functions. The proposed algorithm is designed as full digital blocks and fabricated using 0.35-μm CMOS technology. Experimental results obtained from various samples show that the present method is insensitive to Gaussian and impulsive noises and able to improve the quality of the image by focusing to the appropriate target object.",

keywords = "Autofocus (AF), Focus measure, Fuzzy reasoning, Object detection",

author = "Lee, {Sang Yong} and Yogendera Kumar and Cho, {Ji Man} and Lee, {Sang Won} and Kim, {Soo Won}",

note = "Funding Information: Manuscript received November 17, 2006; revised September 19, 2007. First published April 30, 2008; current version published October 8, 2008. This work was supported by the Ministry of Information and Communication (MIC), Korea, under the IT Foreign Specialist Invitation Program (ITFSIP) supervised by the Institute of Information Technology Assessment (IITA) and Korea IT Industry Promotion Agency (KIPA). This paper was recommended by Associate Editor T. Fujii.",

year = "2008",

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doi = "10.1109/TCSVT.2008.924105",

language = "English",

volume = "18",

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AU - Kumar, Yogendera

AU - Cho, Ji Man

AU - Lee, Sang Won

AU - Kim, Soo Won

N1 - Funding Information: Manuscript received November 17, 2006; revised September 19, 2007. First published April 30, 2008; current version published October 8, 2008. This work was supported by the Ministry of Information and Communication (MIC), Korea, under the IT Foreign Specialist Invitation Program (ITFSIP) supervised by the Institute of Information Technology Assessment (IITA) and Korea IT Industry Promotion Agency (KIPA). This paper was recommended by Associate Editor T. Fujii.

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N2 - A new passive autofocus algorithm consisting of a robust focus measure for object detection and fuzzy reasoning for target selection is presented. The proposed algorithm first detects objects distributed in the image using a mid-frequency discrete cosine transform focus measure and then selects the target object through fuzzy reasoning with three fuzzy membership functions. The proposed algorithm is designed as full digital blocks and fabricated using 0.35-μm CMOS technology. Experimental results obtained from various samples show that the present method is insensitive to Gaussian and impulsive noises and able to improve the quality of the image by focusing to the appropriate target object.

AB - A new passive autofocus algorithm consisting of a robust focus measure for object detection and fuzzy reasoning for target selection is presented. The proposed algorithm first detects objects distributed in the image using a mid-frequency discrete cosine transform focus measure and then selects the target object through fuzzy reasoning with three fuzzy membership functions. The proposed algorithm is designed as full digital blocks and fabricated using 0.35-μm CMOS technology. Experimental results obtained from various samples show that the present method is insensitive to Gaussian and impulsive noises and able to improve the quality of the image by focusing to the appropriate target object.

KW - Autofocus (AF)

KW - Focus measure

KW - Fuzzy reasoning

KW - Object detection

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Enhanced autofocus algorithm using robust focus measure and fuzzy reasoning

Abstract

Keywords

ASJC Scopus subject areas

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