DocumentCode
3283423
Title
An Energy Efficient Binarization Algorithm Based on 2-D Intelligent Block Detection for Complex Texture and Gradient Color Images
Author
Chia-Shaud Hong ; Yen-Hsiang Chen ; Shanq-Jang Ruan
Author_Institution
Dept. of Electron. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan
fYear
2012
fDate
25-28 Aug. 2012
Firstpage
300
Lastpage
303
Abstract
Image binarization involves converting gray-level images into binary ones, which has significantly impacted on intelligent portable devices in recent years. Given the limited memory space and computational power of portable devices, reducing the computational complexity of algorithms which work on embedded systems is of priority concern. This paper proposes a 2-D intelligent block detection algorithm with more accurate region segmentation for document image binarization. By combining merits of global and local algorithms, the proposed approach provides an effective outcome and a low computational cost. As demonstrated by the experimental results, the proposed algorithm is slower than Otsu´s method but 275 times faster than local methods.
Keywords
computational complexity; document image processing; embedded systems; gradient methods; image colour analysis; image segmentation; image texture; text detection; 2D intelligent block detection algorithm; complex texture images; computational complexity reduction; document image binarization; embedded systems; energy efficient binarization algorithm; global algorithms; gradient color images; gray-level images; intelligent portable devices; limited memory space; local algorithms; region segmentation; Algorithm design and analysis; Business; Computational complexity; Image segmentation; Smoothing methods; Standards; Vectors; binarization; business card recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Genetic and Evolutionary Computing (ICGEC), 2012 Sixth International Conference on
Conference_Location
Kitakushu
Print_ISBN
978-1-4673-2138-9
Type
conf
DOI
10.1109/ICGEC.2012.50
Filename
6457270
Link To Document