Grass field detection for TV picture quality enhancement

B. Zafarifar; P.H.N. With, de

doi:10.1109/ICCE.2008.4587982

Grass field detection for TV picture quality enhancement

B. Zafarifar, P.H.N. With, de

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

23 Citations (Scopus)

253 Downloads (Pure)

Abstract

Current TV image enhancement can be improved if the image is analyzed, objects of interest are segmented, and each segment is processed with content-specific enhancement algorithms. In this paper we present an algorithm for segmenting grass areas in video sequences. The system employs multi-scale texture analysis and adaptive color and position models for computing a pixel-based soft segmentation map. Compared to previously reported algorithms, our system shows a clear improvement in the detection result: at 10% false positive rate, the true positive rate of our algorithm yields 91%, vs. 66% and 58% of two existing methods.

Original language	English
Title of host publication	International Conference on Consumer Electronics, 2008. ICCE 2008. Digest of Technical Papers, 9-13 January 2008, Las Vegas, Nevada
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	1-2
ISBN (Print)	978-1-4244-1458-1
DOIs	https://doi.org/10.1109/ICCE.2008.4587982
Publication status	Published - 2008

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title = "Grass field detection for TV picture quality enhancement",

abstract = "Current TV image enhancement can be improved if the image is analyzed, objects of interest are segmented, and each segment is processed with content-specific enhancement algorithms. In this paper we present an algorithm for segmenting grass areas in video sequences. The system employs multi-scale texture analysis and adaptive color and position models for computing a pixel-based soft segmentation map. Compared to previously reported algorithms, our system shows a clear improvement in the detection result: at 10% false positive rate, the true positive rate of our algorithm yields 91%, vs. 66% and 58% of two existing methods.",

author = "B. Zafarifar and {With, de}, P.H.N.",

year = "2008",

doi = "10.1109/ICCE.2008.4587982",

language = "English",

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booktitle = "International Conference on Consumer Electronics, 2008. ICCE 2008. Digest of Technical Papers, 9-13 January 2008, Las Vegas, Nevada",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

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Grass field detection for TV picture quality enhancement. / Zafarifar, B.; With, de, P.H.N.
International Conference on Consumer Electronics, 2008. ICCE 2008. Digest of Technical Papers, 9-13 January 2008, Las Vegas, Nevada. Piscataway: Institute of Electrical and Electronics Engineers, 2008. p. 1-2.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - With, de, P.H.N.

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N2 - Current TV image enhancement can be improved if the image is analyzed, objects of interest are segmented, and each segment is processed with content-specific enhancement algorithms. In this paper we present an algorithm for segmenting grass areas in video sequences. The system employs multi-scale texture analysis and adaptive color and position models for computing a pixel-based soft segmentation map. Compared to previously reported algorithms, our system shows a clear improvement in the detection result: at 10% false positive rate, the true positive rate of our algorithm yields 91%, vs. 66% and 58% of two existing methods.

AB - Current TV image enhancement can be improved if the image is analyzed, objects of interest are segmented, and each segment is processed with content-specific enhancement algorithms. In this paper we present an algorithm for segmenting grass areas in video sequences. The system employs multi-scale texture analysis and adaptive color and position models for computing a pixel-based soft segmentation map. Compared to previously reported algorithms, our system shows a clear improvement in the detection result: at 10% false positive rate, the true positive rate of our algorithm yields 91%, vs. 66% and 58% of two existing methods.

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DO - 10.1109/ICCE.2008.4587982

M3 - Conference contribution

SN - 978-1-4244-1458-1

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EP - 2

BT - International Conference on Consumer Electronics, 2008. ICCE 2008. Digest of Technical Papers, 9-13 January 2008, Las Vegas, Nevada

PB - Institute of Electrical and Electronics Engineers

CY - Piscataway

ER -

Grass field detection for TV picture quality enhancement

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