scholarly journals Improvement of binarization performance using local otsu thresholding

2019 ◽  
Vol 9 (1) ◽  
pp. 264
Author(s):  
Khairun Saddami ◽  
Khairul Munadi ◽  
Yuwaldi Away ◽  
Fitri Arnia
Keyword(s):  
Character Recognition ◽  
Wiener Filter ◽  
Transformation Method ◽  
Wiener Filtering ◽  
Median Filtering ◽  
Important Process ◽  
Connected Component ◽  
Image Subtraction ◽  
Otsu Thresholding ◽  
Processing Steps

<p><span>Ancient document usually contains multiple noises such as uneven-background, show-through, water-spilling, spots, and blur text. The noise will affect the binarization process. Binarization is an extremely important process in image processing, especially for character recognition. This paper presents an improvement to Nina binarization technique. Improvements were achieved by reducing processing steps and replacing median filtering by Wiener filtering. First, the document background was approximated by using Wiener filter, and then image subtraction was applied. Furthermore, the manuscript contrast was adjusted by mapping intensity of image value using intensity transformation method. Next, the local Otsu thresholding was applied. For removing spotting noise, we applied labeled connected component. The proposed method had been testing on H-DIBCO 2014 and degraded Jawi handwritten ancient documents. It performed better regarding recall and precision values, as compared to Otsu, Niblack, Sauvola, Lu, Su, and Nina, especially in the documents with show-through, water-spilling and combination noises.</span></p>

scholarly journals CHARACTER IMAGE SEGMENTATION OF JAVANESE SCRIPT USING CONNECTED COMPONENT METHOD

2019 ◽  
Vol 12 (2) ◽  
pp. 67
Author(s):  
Yuna Sugianela ◽  
Nanik Suciati
Keyword(s):  
Image Segmentation ◽  
Character Recognition ◽  
Region Of Interest ◽  
Character Segmentation ◽  
Translation System ◽  
Important Process ◽  
Connected Component ◽  
Projection Profile ◽  
Centroid Distance ◽  
Meaningful Word

Automation of Javanese script translation is needed to make it easier for people to understand the meaning of ancient Javanese script. By using Javanese script image as input, the translation system generally consists of character segmentation, character recognition, and combining the recognized characters as a meaningful word. The segmentation which obtains region of interest of each character, is an important process in the translation system. In the previous research, segmentation using projection profile method can separate each character well. The method can overcome characters overlapping, but it still produces truncated characters. In this study, we proposed a new segmentation to reduce the truncated character. The first step of the proposed method is pre-processing that consists of converting input into binary image and cleaning noises. The next step is to determine the connected component labels, which further perform as candidate of characters. Some of the candidates are still represented by more than one labels, so that we need a process to merge the connected component labels that have centroid distance less than threshold. We evaluate the proposed method using Intersection over Union (IoU). The evaluation shows the best accuracy 93,26%.

scholarly journals Unconstrained Handwritten Text Line Segmentation for Kannada Language

2019 ◽  
Vol 8 (12) ◽  
pp. 953-956
Keyword(s):  
Character Recognition ◽  
Recognition System ◽  
Text Line ◽  
Connected Component ◽  
Horizontal Projection ◽  
Text Documents ◽  
Handwritten Text ◽  
Kannada Language ◽  
System Separation ◽  
Line Segmentation

Segmentation is division of something into smaller parts and one of the Component of character recognition system. Separation of characters, words and lines are done in Segmentation from text documents. character recognition is a process which allows computers to recognize written or printed characters such as numbers or letters and to change them into a form that the computer can use. the accuracy of OCR system is done by taking the output of an OCR run for an image and comparing it to the original version of the same text. The main aim of this paper is to find out the various text line segmentations are Projection profiles, Weighted Bucket Method. Proposed method is horizontal projection profile and connected component method on Handwritten Kannada language. These methods are used for experimentation and finally comparing their accuracy and results.

Synchrosqueezing Transform Based Powerline Interference Reduction in ECG Recording

2020 ◽  
Vol 10 (10) ◽  
pp. 2259-2273
Author(s):  
M. Suresh Kumar ◽  
G. Krishnamoorthy ◽  
D. Vaithiyanathan
Keyword(s):  
Operation Mode ◽  
Wiener Filter ◽  
Wiener Filtering ◽  
Ecg Signal ◽  
Intrinsic Mode Functions ◽  
Ecg Signals ◽  
Mode Decomposition ◽  
Synchrosqueezing Transform ◽  
Signal Mode ◽  
Powerline Interference

This paper presents an adaptive ECG enhancement procedure based on Synchrosqueezing Transform (SST) to eliminate Powerline interference (PLI) from ECG signal. This work also incorporates the principles of modified discrete cosine transform (MDCT) and wiener filter. PLI is a major source of artifacts in the ECG signal which can affect its interpretation. Separating PLI from ECG signal poses a great challenge in the ECG analysis. The existing PLI removal techniques suffer from two major drawbacks such as Mode Mixing, inability to deal with non-stationary characteristics of signal. In this paper, we propose SST based wiener filtering approaches which can overcome the limitation of existing PLI suppression techniques. The proposed approaches undergo three stages of operation: mode decomposition, mode determination and peak restoration to filter out PLI from ECG recording. The mode decomposition uses SST to decompose the corrupted ECG signal into a sum of well separated intrinsic mode functions (IMFs). The objective is to filter out PLI from these IMFs. To do so, mode determination step which is based on Kurtosis and Crest factor is applied to categorize decomposition result into groups such as signal mode and noisy mode. Direct subtraction of the noisy mode from the corrupted ECG observation results in ECG signal with reduced peak since noise mode carries part of signal components in addition to interference. Hence, to restore the peak, wiener filter is applied on noisy mode to estimate actual PLI component. Finally, Noise free ECG signal is reconstructed by subtracting estimated PLI from the corrupted ECG signal. This paper discusses four possible PLI suppression methods which are derived by combining SST domain with wiener filter in various ways. Simulations are carried out to test the effectiveness of proposed methods. It is evident from the simulation results that the proposed methods can remove PLI of 50 Hz and its harmonics. The proposed techniques effectively removed PLI in both real and artificial ECG signals and to test its performance they are compared with state of the art methods. The SST based filtering methods outperformed other methods under the condition of PLI frequency variations. The experimental results also suggest that the SST based wiener filtering with modified reference approach offers better PLI suppression than all other methods.

scholarly journals Deconvolution of Defocused Image with Multivariate Local Polynomial Regression and Iterative Wiener Filtering in DWT Domain

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Liyun Su ◽  
Fenglan Li
Keyword(s):  
Polynomial Regression ◽  
Wiener Filter ◽  
Simulated Data ◽  
Wiener Filtering ◽  
Image Deconvolution ◽  
Local Polynomial Regression ◽  
Local Polynomial ◽  
Multivariate Local Polynomial Regression ◽  
Restoration Method ◽  
Defocused Image

A novel semiblind defocused image deconvolution technique is proposed, which is based on multivariate local polynomial regression (MLPR) and iterative Wiener filtering (IWF). In this technique, firstly a multivariate local polynomial regression model is trained in wavelet domain to estimate defocus parameter. After obtaining the point spread function (PSF) parameter, iterative wiener filter is adopted to complete the restoration. We experimentally illustrate its performance on simulated data and real blurred image. Results show that the proposed PSF parameter estimation technique and the image restoration method are effective.

scholarly journals Character Segmentation and Recognition of Marathi Language

2021 ◽  
Vol 9 (12) ◽  
pp. 1544-1551
Author(s):  
Saurabh Ravindra Nikam
Keyword(s):  
Image Segmentation ◽  
Character Recognition ◽  
Structural Features ◽  
Input Image ◽  
Character Segmentation ◽  
Important Process ◽  
Critical Task ◽  
The Individual ◽  
Segmentation Image

Abstract: In this paper Segmentation is one the most important process which decides the success of character recognition fashion. Segmentation is used to putrefy an image of a sequence of characters into sub images of individual symbols by segmenting lines and words. In segmentation image is partitioned into multiple corridor. With respect to the segmentation of handwritten words into characters it's a critical task because of complexity of structural features and kinds in writing styles. Due to this without segmentation these touching characters, it's delicate to fete the individual characters, hence arises the need for segmentation of touching characters in a word. Then we consider Marathi words and Marathi Numbers for segmentation. The algorithm is use for Segmentation of lines and also characters. The segmented characters are also stores in result variable. First it Separate the lines and also it Separate the characters from the input image. This procedure is repeated till end of train. Keywords: Image Segmentation, Handwritten Marathi Characters, Marathi Numbers, OCR.

An Enhanced Approach for Number Plate Detection and Recognition

2020 ◽  
Vol 13 ◽  
Author(s):  
Diksha Kurchaniya ◽  
Mohd. Aquib Ansari ◽  
Durga Patel
Keyword(s):  
Character Recognition ◽  
High Speed ◽  
Detection System ◽  
Wiener Filter ◽  
Noise Removal ◽  
Motor Vehicles ◽  
Detection Accuracy ◽  
Morphological Operations ◽  
Wide Range ◽  
High Speed Vehicle

Introduction: The number of vehicles is increasing day by day in our life. The vehicle may violate traffic rules and cause accidents. The automatic number plate detection system (ANPR) plays a significant role to identify these vehicles. Number plate detection is very difficult sometimes because each country has its own format for representing the number plate and font types and sizes may also vary for different vehicles. The number of ANPR systems is available nowadays but still, it is a big problem to detect the number plate correctly in various scenarios like high-speed vehicle, number plate language, etc. Methods: In the development of this method, we mainly used wiener filter for noise removal, morphological operations for number plate localization, connected component algorithm for character segmentation, and template based matching for character recognition. Results: Our proposed methodology is providing promising results in terms of detection accuracy. Discussion: The automatic number plate detection system (ANPR) has wide range of applications because the license number is the crucial, commonly putative and essential identifier of motor vehicles. These applications include ticketless parking fee management, parking access automation, car theft prevention, security guide assistance, Motorway Road Tolling, Border Control, Journey Time Measurement, Law Enforcement and many more. Conclusion: In this paper, an enhanced approach of automatic number plate detection system is proposed using some different techniques which not only detect the number plate of the vehicle but also recognize each character present in the detected number plate image.

An Effective Edge and Texture Based Approach towards Curved Videotext Detection and Extraction

2015 ◽  
Vol 4 (3) ◽  
pp. 1-29 ◽  
Author(s):  
P. Sudir ◽  
M. Ravishankar
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Connected Component ◽  
Low Contrast ◽  
Video Frames ◽  
Video Text Detection ◽  
Indexing And Retrieval ◽  
Video Indexing And Retrieval ◽  
Curved Text ◽  
New Framework

In present day video text greatly helps video indexing and retrieval system as they often carry significant semantic information. Video text analysis is challenging due to varying background, multiple orientations and low contrast between text and non-text regions. Proposed approach explores a new framework for curved video text detection and recognition where from the observation that curve text regions can be well defined by edges size and uniform texture, Probable curved text edge detection is accomplished by processing wavelet sub bands followed by text localization by utilizing fast texture descriptor LU-transform. Binarization is achieved by maximal H-transform. A Connected Component filtering method followed by B-Spline curve fitting on centroid of each character vertically aligns each oriented character. The aligned text string is recognized by optical character recognition (OCR). Experiments on various curved video frames shows that proposed method is efficacious and robust in detecting and recognizing curved videotext.

Research on Image Restoration Methods

2015 ◽  
Vol 742 ◽  
pp. 277-280
Author(s):  
Yu Bing Dong ◽  
Hua Xun Zhang ◽  
Ying Sun
Keyword(s):  
Image Restoration ◽  
Histogram Equalization ◽  
New Method ◽  
Wiener Filtering ◽  
Median Filtering ◽  
Inverse Filtering ◽  
Matlab Simulation ◽  
Paper Degradation ◽  
Restoration Method ◽  
Restoration Model

In the paper, degradation and restoration model is introduced. Image restoration method using inverse filtering and using wiener filtering are studied and implemented. A new method of image restoration is proposed by combining histogram equalization and median filtering. Comparing three methods by MATLAB simulation, the results show that the new method can effectively restore degradation image with comparatively high restoration efficiency.

Research of Denoising Technology about Wavelet Analysis with Wiener Filter

2013 ◽  
Vol 333-335 ◽  
pp. 597-600
Author(s):  
Yao Bin Hu ◽  
Liang Bin Hu ◽  
Qiang Cheng
Keyword(s):  
Signal Processing ◽  
Wavelet Analysis ◽  
White Noise ◽  
Frequency Spectrum ◽  
Wiener Filter ◽  
Power Line ◽  
Wiener Filtering ◽  
Power Line Communication ◽  
Denoising Method

Interfering noise of power line is one of the important factors which affects the quality of power line communication (PLC). Its frequency spectrum has the character of the 1/f process and the great autocorrelation. The wavelet analysis is an important signal-processing tool. Selecting suitable wavelet analysis can turn non-white noise to white noise, followed by wiener filtering, we can achieve the purpose of denoising. This paper introduces a denoising method of combining wavelet analysis with wiener filtering. Experiment proves this method has a strong feasibility and practical value.

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