An interactive document image description for OCR of handwritten forms

Image quality assessment has been a very active research area in the field of image processing, and there have been numerous methods proposed. However, most of the existing methods focus on digital images that only or mainly contain pictures or photos taken by digital cameras. Traditional approaches evaluate an input image as a whole and try to estimate a quality score for the image, in order to give viewers an idea of how “good” the image looks. In this paper, we mainly focus on the quality evaluation of contents of symbols like texts, bar-codes, QR-codes, lines, and hand-writings in target images. Estimating a quality score for this kind of information can be based on whether or not it is readable by a human, or recognizable by a decoder. Moreover, we mainly study the viewing quality of the scanned document of a printed image. For this purpose, we propose a novel image quality assessment algorithm that is able to determine the readability of a scanned document or regions in a scanned document. Experimental results on some testing images demonstrate the effectiveness of our method.

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An Adaptive Binarization Method for Cost-efficient Document Image System in Wavelet Domain

Journal of Imaging Science and Technology ◽

10.2352/j.imagingsci.technol.2020.64.3.030401 ◽

2020 ◽

Vol 64 (3) ◽

pp. 30401-1-30401-14 ◽

Cited By ~ 1

Author(s):

Chih-Hsien Hsia ◽

Ting-Yu Lin ◽

Jen-Shiun Chiang

Keyword(s):

Wavelet Transform ◽

Discrete Wavelet Transform ◽

Document Image ◽

Background Information ◽

Raspberry Pi ◽

Discrete Wavelet ◽

Image System ◽

Low Frequencies ◽

Cost Efficient ◽

Binarization Method

Abstract In recent years, the preservation of handwritten historical documents and scripts archived by digitized images has been gradually emphasized. However, the selection of different thicknesses of the paper for printing or writing is likely to make the content of the back page seep into the front page. In order to solve this, a cost-efficient document image system is proposed. In this system, the authors use Adaptive Directional Lifting-Based Discrete Wavelet Transform to transform image data from spatial domain to frequency domain and perform on high and low frequencies, respectively. For low frequencies, the authors use local threshold to remove most background information. For high frequencies, they use modified Least Mean Square training algorithm to produce a unique weighted mask and perform convolution on original frequency, respectively. Afterward, Inverse Adaptive Directional Lifting-Based Discrete Wavelet Transform is performed to reconstruct the four subband images to a resulting image with original size. Finally, a global binarization method, Otsu’s method, is applied to transform a gray scale image to a binary image as the output result. The results show that the difference in operation time of this work between a personal computer (PC) and Raspberry Pi is little. Therefore, the proposed cost-efficient document image system which performed on Raspberry Pi embedded platform has the same performance and obtains the same results as those performed on a PC.

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A Fast Non-destructive Algorithm for Image Description Based on Improved Wavelet Moment Features

ACTA AUTOMATICA SINICA ◽

10.3724/sp.j.1004.2009.01278 ◽

2009 ◽

Vol 35 (10) ◽

pp. 1278-1282

Author(s):

Jia-Min LIU ◽

Hai-Jun XIE ◽

Qiang LIU ◽

Sheng-Jun ZHU ◽

Wei ZHANG

Keyword(s):

Image Description ◽

Moment Features ◽

Non Destructive

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Secure exact authentication in binary document image watermarking

IET International Conference on Visual Information Engineering (VIE 2006) ◽

10.1049/cp:20060497 ◽

2006 ◽

Cited By ~ 2

Author(s):

N.B. Puhan ◽

A.T.S. Ho

Keyword(s):

Image Watermarking ◽

Document Image

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An enhanced binarization framework for degraded historical document images

EURASIP Journal on Image and Video Processing ◽

10.1186/s13640-021-00556-4 ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Wei Xiong ◽

Lei Zhou ◽

Ling Yue ◽

Lirong Li ◽

Song Wang

Keyword(s):

Document Image ◽

Morphological Operations ◽

Document Images ◽

Minimum Entropy ◽

Stroke Width ◽

Background Estimation ◽

Structuring Element ◽

Document Image Binarization ◽

Benchmark Datasets ◽

Stroke Width Transform

AbstractBinarization plays an important role in document analysis and recognition (DAR) systems. In this paper, we present our winning algorithm in ICFHR 2018 competition on handwritten document image binarization (H-DIBCO 2018), which is based on background estimation and energy minimization. First, we adopt mathematical morphological operations to estimate and compensate the document background. It uses a disk-shaped structuring element, whose radius is computed by the minimum entropy-based stroke width transform (SWT). Second, we perform Laplacian energy-based segmentation on the compensated document images. Finally, we implement post-processing to preserve text stroke connectivity and eliminate isolated noise. Experimental results indicate that the proposed method outperforms other state-of-the-art techniques on several public available benchmark datasets.

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Invariant Image Representation Using Novel Fractional-Order Polar Harmonic Fourier Moments

Sensors ◽

10.3390/s21041544 ◽

2021 ◽

Vol 21 (4) ◽

pp. 1544

Author(s):

Chunpeng Wang ◽

Hongling Gao ◽

Meihong Yang ◽

Jian Li ◽

Bin Ma ◽

...

Keyword(s):

Image Reconstruction ◽

Fractional Order ◽

Continuous Functions ◽

Kernel Functions ◽

Superior Performance ◽

Image Description ◽

Orthogonal Moments ◽

Integer Order ◽

Geometric Invariance ◽

Order Continuous

Continuous orthogonal moments, for which continuous functions are used as kernel functions, are invariant to rotation and scaling, and they have been greatly developed over the recent years. Among continuous orthogonal moments, polar harmonic Fourier moments (PHFMs) have superior performance and strong image description ability. In order to improve the performance of PHFMs in noise resistance and image reconstruction, PHFMs, which can only take integer numbers, are extended to fractional-order polar harmonic Fourier moments (FrPHFMs) in this paper. Firstly, the radial polynomials of integer-order PHFMs are modified to obtain fractional-order radial polynomials, and FrPHFMs are constructed based on the fractional-order radial polynomials; subsequently, the strong reconstruction ability, orthogonality, and geometric invariance of the proposed FrPHFMs are proven; and, finally, the performance of the proposed FrPHFMs is compared with that of integer-order PHFMs, fractional-order radial harmonic Fourier moments (FrRHFMs), fractional-order polar harmonic transforms (FrPHTs), and fractional-order Zernike moments (FrZMs). The experimental results show that the FrPHFMs constructed in this paper are superior to integer-order PHFMs and other fractional-order continuous orthogonal moments in terms of performance in image reconstruction and object recognition, as well as that the proposed FrPHFMs have strong image description ability and good stability.

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Document Image Classification: Progress over Two Decades

Neurocomputing ◽

10.1016/j.neucom.2021.04.114 ◽

2021 ◽

Author(s):

Li Liu ◽

Zhiyu Wang ◽

Taorong Qiu ◽

Qiu Chen ◽

Yue Lu ◽

...

Keyword(s):

Image Classification ◽

Document Image

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