Citation

Salis, Vimuktha Evangeleen and Sayeed, Md Shohel and Samraj, Andrews and Jathanna, Vineetha Edwina Scene Text Extraction from Natural Images Using a 2D Haar Wavelet Transform Pipeline. International Journal of Computer Information Systems and Industrial Management Applications, 18 (7). pp. 1240-1261. ISSN 2150-7988

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Abstract

Text extraction from natural scene images is a fundamental task in computer vision with applications in areas such as autonomous navigation, assistive reading for the visually impaired and real-time translation. Natural scenes pose serious challenges such as cluttered background, uneven illumination, perspective distortion and multiscale and multi-oriented text. In this paper, a new training-free signal-processing framework using the two-dimensional Haar wavelet transform is proposed for the scene text extraction. The pipeline consists of a luminance based gray scale conversion and an adaptive wiener filtering for noise suppression followed by haar wavelet decomposition into directional sub-bands. Sobel edge detection with sub-band fusion highlights the text boundaries. The morphological dilation operation is applied, then connected component analysis with a geometric density filter and Otsu binarization is performed to isolate the candidate regions for Tesseract recognition. On three standard benchmark datasets the method achieved F-measures of 89.5, 86.8 and 80.6 percent, which makes it competitive to both classical and deep-learning approaches while requiring no training data.

Item Type:	Article
Uncontrolled Keywords:	Scene text extraction, Haar wavelet transform, Wiener filter, Sobel edge detection, Morphological dilation, Connected component analysis, Optical character recognition
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	04 Sep 2026 02:35
Last Modified:	04 Sep 2026 02:35
URII:	http://shdl.mmu.edu.my/id/eprint/16682

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