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binarization algorithm for Document Image with Complex Background 9

Binarization Algorithm for Document Image with Complex Backg...

9th International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR) - Pattern Recognition and Computer Vision

作者： Miao, Shaojun Lu, Tongwei Min, Feng Wuhan Inst Technol Sch Comp Sci & Engn Wuhan 430205 Peoples R China Wuhan Inst Technol Hubei Key Lab Intelligent Robot Wuhan 430205 Peoples R China

ISBN: (纸本)9781510600546

The most important step in image preprocessing for Optical Character Recognition (OCR) is binarization. Due to the complex background or varying light in the text image, binarization is a very difficult problem. This paper presents the improved binarization algorithm. The algorithm can be divided into several steps. First, the background approximation can be obtained by the polynomial fitting, and the text is sharpened by using bilateral filter. Second, the image contrast compensation is done to reduce the impact of light and improve contrast of the original image. Third, the first derivative of the pixels in the compensated image are calculated to get the average value of the threshold, then the edge detection is obtained. Fourth, the stroke width of the text is estimated through a measuring of distance between edge pixels. The final stroke width is determined by choosing the most frequent distance in the histogram. Fifth, according to the value of the final stroke width, the window size is calculated, then a local threshold estimation approach can begin to binaries the image. Finally, the small noise is removed based on the morphological operators. The experimental result shows that the proposed method can effectively remove the noise caused by complex background and varying light.

关键词： binarization algorithm bilateral filter Iteration method edge detection local threshold

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A New Box-Counting-Based-Image Fractal Dimension Estimation Method for Discharges Recognition on Polluted Insulator Model

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IET SCIENCE MEASUREMENT & TECHNOLOGY 2025年第1期19卷

作者： Ferrah, Imene Benmahamed, Youcef Jahanger, Hayder K. Teguar, Madjid Kherif, Omar Ecole Natl Polytech Lab Rech Electrotech Algiers Algeria Swansea Univ Dept Elect & Elect Engn Swansea Wales Univ Warwick Sch Engn Coventry England Cardiff Univ Adv High Voltage Engn Res Ctr Cardiff Wales

This study presents an innovative approach to identify electrical discharges by proposing an algorithm incorporating fractal geometry concepts. Based on the box-counting method, our algorithm is developed to detect and track the progression of electrical discharges leading to flashover. This is achieved by calculating the fractal dimension of discharge images which are visual representations of electrical activity recorded during experiments on a planar glass insulator model subjected to different levels of contamination. First, the RGB image is transformed into a binary matrix using the NIBLAK binarization algorithm. Subsequently, the acquired matrix is converted into a square matrix, and its fractal dimension is computed for various resolutions. The final fractal dimension of the image is calculated using the least squares method. This latter is applied to the fractal dimensions (FDs) across all resolutions. According to our algorithm, discharge images have FD values ranging from 1.15 to 1.25. FD increases are observed with applied voltage and non-soluble deposit density (NSDD). The density and activity of discharges also increase with FD. Specifically, a discharge is considered "no-arc" if FD is less than 1.2 and "arc" otherwise.

关键词： arcing discharge binarization algorithm box-counting method flashover fractal dimension insulator pollution Niblack method

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binarization of optical fringe patterns with intensity inhomogeneities based on modified FCM algorithm

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OPTICS AND LASERS IN ENGINEERING 2019年第Dec.期123卷 14-19页

作者： Chen, Mingming Tang, Chen Xu, Min Lei, Zhenkun Tianjin Univ Sch Elect & Informat Engn Tianjin 300072 Peoples R China Dalian Univ Technol State Key Lab Struct Anal Ind Equipment Dalian 116024 Peoples R China

binarization of fringe patterns is a commonly used process in the fringe skeleton method for optical fringe pattern analysis. Most of the existing binarization algorithms of fringe patterns are based on the determination of gray level threshold. However, spatial intensity inhomogeneity induced by the uneven illumination makes the gray level threshold hard to determine. In this paper, we present a method for the binarization of fringe patterns based on a modified Fuzzy c-means clustering (FCM) algorithm. This method permits the clustering of pixels influenced by their immediate surroundings. The pixels in the fringe pattern are clustered into white fringes and black fringes without calculating thresholds. We evaluate the performance of this method by applying it to computer-simulated and real fringe patterns. Experimental results demonstrate that the proposed method can achieve the desired binarization results and perform better than the previous binarization methods, under nonuniform illumination conditions.

关键词： Fringe analysis Speckle interferometry binarization algorithm Fuzzy c-means clustering

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Document binarization with automatic parameter tuning

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INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION 2013年第3期16卷 247-258页

作者： Howe, Nicholas R. Smith Coll Northampton MA 01063 USA

Document analysis systems often begin with binarization as a first processing stage. Although numerous techniques for binarization have been proposed, the results produced can vary in quality and often prove sensitive to the settings of one or more control parameters. This paper examines a promising approach to binarization based upon simple principles, and shows that its success depends most significantly upon the values of two key parameters. It further describes an automatic technique for setting these parameters in a manner that tunes them to the individual image, yielding a final binarization algorithm that can cut total error by one-third with respect to the baseline version. The results of this method advance the state of the art on recent benchmarks.

关键词： tuning binarization algorithm AUTOMATIC binarization state of the art Global Error

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Regional Context Model and Dynamic Huffman binarization for Adaptive Entropy Coding of Multimedia

Regional Context Model and Dynamic Huffman Binarization for ...

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IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： Wu, Jiangming Dai, Wenrui Xiong, Hongkai Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China

ISBN: (纸本)9781479916542

Classical context modeling and binarization algorithms on multimedia do not fully exploit their spatial correlations under the sequential assumption. This paper proposes a novel entropy coding scheme incorporating regional context modeling (RCM) and dynamic Huffman binarization (DHB) for multimedia. RCM evaluates the context order with the line distance in Cartesian coordinate system, so that the 2-D spatial correlations can be directly exploited. RCM predicts each symbol with the weighted estimation based on the line distance and appearing frequency of its context, which coincides with the principle for context-based prediction. On the other hand, DHB is proposed to adaptively assign the length of bins based on the estimated probability of symbols for coding. For optimal prediction and coding, frequent symbols are assigned with short bins to constrain the propagation of code redundancy. Applied into multimedia coding, extensive experimental results show that the proposed scheme achieves better coding performance than the benchmark coders.

关键词： Adaptation models Context Context modeling Encoding Heuristic algorithms Multimedia communication Redundancy Context modeling MULTI-MEDIA SYSTEM Multimedia communications Heuristic algorithms Entropy coding redundancy Adaptation models rapid compression machine Reliability centred plant maintenance Signs and symbols binarization coding binarization algorithm Bins Cartesian coordinate system

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Experimental study on the law of transitional gas flow in porous media

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JOURNAL OF PETROLEUM EXPLORATION AND PRODUCTION TECHNOLOGY 2023年第2期13卷 723-733页

作者： Miao, Jian Jia, Haojie Li, Peibo Feng, Guanzheng Henan Polytech Univ Sch Safety Sci & Engn Jiaozuo 454003 Henan Peoples R China Shandong Management Univ Sch Intelligent Engn Jinan 250357 Peoples R China China Univ Min & Technol State Key Lab Geomech & Deep Underground Engn Xuzhou 221116 Jiangsu Peoples R China Second Construct Engn Ltd Co China Construct Engn Bur 3 Wuhan 430074 Peoples R China

There are many nanoscale pores in deep low permeability coal seams. The flow of coalbed methane (gas) in nanoscale pores belongs to the gas flow in porous media with medium and high Knudsen numbers. Its flow mechanism is one of the key unsolved scientific problems. In order to explore the gas transport law in nanopores of coal, a gas transport model based on microscopic boundary restriction was adopted to describe the gas flow law, and its rationality was verified by experimental data. The Field Emission Scanning Electron Microscope was used to scan the nanopores of customized anodized aluminum membrane. Then, the Maximally Stable Extremal Regions (MSER) algorithm of MATLAB and binarization algorithm were employed to quantify the pore structure parameters (equivalent pore size and porosity) of the membrane nanoscale pores. Finally, PMI micro-flow permeability tester was used to carry out different rarefied degree gas penetration experiments through anodized aluminum membranes, and the adopted gas transport model was verified. The results show that the binarization method is more accurate to characterize sample whose theoretical pore sizes are 20-35 nm, while MSER characterizes samples whose theoretical pore sizes are 110-150 nm and 200-300 nm more accurately. In other words, binarization method is more accurate for characterizing mesopores, while MSER algorithm is more accurate for macropores. The results have important reference value for more accurate extraction of nanopore parameters of porous media. Compared with traditional gas transport model, the adopted model considering the microscopic boundary restriction in this paper is closer to the experimental results. Moreover, it is suitable for describing the gas flow law in multiscale nanopores. The study provided important guiding significance for ascertaining the gas migration law in low permeability coal seam, improving the prediction accuracy of gas extraction and taking effective measures to increase producti

关键词： Transitional flow Microscopic boundary restriction Maximally Stable Extremal Regions binarization algorithm

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Robust table recognition for printed document images

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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2020年第4期17卷 3203-3223页

作者： Liang, Qiaokang Peng, Jianzhong Li, Zhengwei Xie, Daqi Sun, Wei Wang, Yaonan Zhang, Dan Hunan Univ Coll Elect & Informat Engn Changsha 410082 Peoples R China Hunan Univ Natl Engn Lab Robot Vis Percept & Control Changsha 410082 Peoples R China Univ Alberta Dept Mech Engn Edmonton AB T6G 2R3 Canada York Univ Dept Mech Engn Toronto ON M3J 1P3 Canada

The recognition and analysis of tables on printed document images is a popular research field of the pattern recognition and image processing. Existing table recognition methods usually require high degree of regularity, and the robustness still needs significant improvement. This paper focuses on a robust table recognition system that mainly consists of three parts: Image preprocessing, cell location based on contour mutual exclusion, and recognition of printed Chinese characters based on deep learning network. A table recognition app has been developed based on these proposed algorithms, which can transform the captured images to editable text in real time. The effectiveness of the table recognition app has been verified by testing a dataset of 105 images. The corresponding test results show that it could well identify high-quality tables, and the recognition rate of low-quality tables with distortion and blur reaches 81%, which is considerably higher than those of the existing methods. The work in this paper could give insights into the application of the table recognition and analysis algorithms.

关键词： table image recognition binarization algorithm deep learning recurrent neural network character recognition

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CLASSIFICATION-BASED SEGMENTATION OF ZIP CODES

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS 1993年第5期23卷 1437-1443页

作者： SAIFULLAH, Y MANRY, MT Department of Electrical Engineering University of Texas Arlington TX USA

In this paper a system for the segmentation of unconstrained handwritten ZIP codes is presented. A binarization algorithm is described that utilizes the bimodal nature of the input 256 gray level histogram. ZIP code images are scaled to a standard size for further processing. Objects that are not comparable to the size of numerals are classified as noise and removed. An algorithm that segments broken or touching characters is presented. Several trial segmentations of each ZIP code are produced. A character classifier is used to determine which trial segmentation is most likely to be correct.

关键词： binarization algorithm Codes Numerals standard sizes ZIPPERS

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PSYCHOPHYSICAL VALIDATION OF A DIGITAL METHOD TO ASSESS ILL-DEFINED VISUAL BOUNDARIES: AN EXAMPLE WITH FABRIC OPENNESS FACTOR

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JOURNAL OF SENSORY STUDIES 2015年第6期30卷 512-521页

作者： Tapias, Montserrat Rallo, Miquel Escofet, Jaume Univ Politecn Cataluna Opt & Optometria Barcelona Spain Univ Politecn Cataluna Matemat Aplicada Barcelona Spain

Fabric openness factor (OF) is the fraction of the web area that is uncovered by yarns. OF is a critical feature regarding the end-use performance of the fabric and should be accurately assessed. However, digital OF estimates yielded by image binarization algorithms differ among them depending on the criteria used, mainly due to ill-defined boundaries, thus precluding a straightforward assessment of the actual fabric OF value. Lacking any standard to compare actual OF values with measured OF values, we addressed the validation procedure of the digital assessment method from visual OF estimates. OF of 81 distinct fabric samples was evaluated from digital images by a panel of 18 observers using visual binarization technique. Following the psychophysical models of Fechner and Stevens, these visual estimates were correlated with digital estimates yielded by several binarization algorithms. Stevens' psychophysical model and an automatic binarization algorithm developed by us scored the highest correlation.

关键词： Visualization Yarns Stevens binarization algorithm Digital images binarization technique

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Key Technology in Detecting and Eliminating Isomerism Fibre in Cotton

<bold>Key Technology in Detecting and Eliminating Isomerism ...

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8th International Conference on Electronic Measurement and Instruments

作者： Li Yujun Liang Kun Bai HuaYu Xian Univ Technol Sch Automat & Informat Engn Xian 710048 Peoples R China Xian Univ Technol Sch Comp Sci & Engn Xian 710048 Peoples R China

ISBN: (纸本)1424411351

Framework and working principle of detecting and eliminating isomerism fibre in cotton system online is introduced and several key technologies involved in its design are analyzed. Experiment studies are implemented and advances solved scheme. In the technologic methods flow of cleaning and rippling the cotton, cotton has been loosed enough and impurity is removed. Then a linear CCD (charge coupled device) camera is used to capture the image of cotton and foreign fibre. from the camera. The images are sent to the industry, control computer through a high-speed frame grabber acquires digital card and operated in computer. HSI (Hue, saturation, Intensity) color model threshold method and binarization algorithm are used to distinguish cotton with isomerism fibre. When finding the foreign fibre, the computer will send out an instrument to drive the corresponding position gas-act electromagnetism valve to act and using high-pressure gas to jet it out to the trash box. Through a series of experiments and locale debug analysis, a sample machine system is established. Through testing it can reach the need of control and exact distinguish die cotton and isomerism fibre in real time and eliminate it.

关键词： linear CCD HSI color model threshold value binarization algorithm

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