The recognition of Hangul Image is more difficult compared with that of Latin. It could be recognized from the structural arrangement. Hangul is arranged from two dimensions while Latin is only from the left to the right. The current research creates a system to convert Hangul image into Latin text in order to use it as a learning material on reading Hangul. In general, image recognition system is divided into three steps. The first step is preprocessing, which includes binarization, segmentation through connected component-labeling method, and thinning with Zhang Suen to decrease some pattern information. The second is receiving the feature from every single image, whose identification process is done through chain code method. The third is recognizing the process using Support Vector Machine (SVM) with some kernels. It works through letter image and Hangul word recognition. It consists of 34 letters, each of which has 15 different patterns. The whole patterns are 510, divided into 3 data scenarios. The highest result achieved is 94,7% using SVM kernel polynomial and radial basis function. The level of recognition result is influenced by many trained data. Whilst the recognition process of Hangul word applies to the type 2 Hangul word with 6 different patterns. The difference of these patterns appears from the change of the font type. The chosen fonts for data training are such as Batang, Dotum, Gaeul, Gulim, Malgun Gothic. Arial Unicode MS is used to test the data. The lowest accuracy is achieved through the use of SVM kernel radial basis function, which is 69%. The same result, 72 %, is given by the SVM kernel linear and polynomial.
Improved block based segmentation for jpeg compressed document imageseSAT Journals
Abstract
Image Compression is to minimize the size in bytes of a graphics file without degrading the quality of the image to an unacceptable
level. The compound image compression normally based on three classification methods that is object based, layer based and block
based. This paper presents a block-based segmentation. for visually lossless compression of scanned documents that contain not only
photographic images but also text and graphic images. In low bit rate applications they suffer with undesirable compression artifacts,
especially for document images. Existing methods can reduce these artifacts by using post processing methods without changing the
encoding process. Some of these post processing methods requires classification of the encoded blocks into different categories.
Keywords- AC energy, Discrete Cosine Transform (DCT), JPEG, K-means clustering, Threshold value
Text-Image Separation in Document Images using Boundary/Perimeter DetectionIDES Editor
Document analysis plays an important role in office
automation, especially in intelligent signal processing. The
proposed system consists of two modules: block segmentation
and block identification. In this approach, first a document is
segmented into several non-overlapping blocks by utilizing a
novel recursive segmentation technique, and then extracts
the features embedded in each segmented block are extracted.
Two kinds of features, connected components and image
boundary/perimeter features are extracted. Document with
text inside image pose limitations in earlier reported literature.
This is taken care of by applying additional pass of the Run
Length Smearing on the extracted image that contains text.
Proposed scheme is independent of type and language of the
document.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
New Approach of Preprocessing For Numeral RecognitionIJERA Editor
The present paper proposes a new approach of preprocessing for handwritten, printed and isolated numeral
characters. The new approach reduces the size of the input image of each numeral by discarding the redundant
information. This method reduces also the number of features of the attribute vector provided by the extraction
features method. Numeral recognition is carried out in this work through k nearest neighbors and multilayer
perceptron techniques. The simulations have obtained a good rate of recognition in fewer running time.
OCR for Gujarati Numeral using Neural Networkijsrd.com
This papers functions within to reduce individuality popularity (OCR) program for hand-written Gujarati research. One can find so much of work for Indian own native different languages like Hindi, Gujarati, Tamil, Bengali, Malayalam, Gurumukhi etc., but Gujarati is a vocabulary for which hardly any work is traceable especially for hand-written individuals. Here in this work a nerve program is provided for Gujarati hand-written research popularity. This paper deals with an optical character recognition (OCR) system for handwritten Gujarati numbers. A several break up food ahead nerve program is suggested for variation of research. The functions of Gujarati research are abstracted by four different details of research. Reduction and skew- changes are also done for preprocessing of hand-written research before their variation. This work has purchased approximately 81% of performance for Gujarati handwritten numerals.
Improved block based segmentation for jpeg compressed document imageseSAT Journals
Abstract
Image Compression is to minimize the size in bytes of a graphics file without degrading the quality of the image to an unacceptable
level. The compound image compression normally based on three classification methods that is object based, layer based and block
based. This paper presents a block-based segmentation. for visually lossless compression of scanned documents that contain not only
photographic images but also text and graphic images. In low bit rate applications they suffer with undesirable compression artifacts,
especially for document images. Existing methods can reduce these artifacts by using post processing methods without changing the
encoding process. Some of these post processing methods requires classification of the encoded blocks into different categories.
Keywords- AC energy, Discrete Cosine Transform (DCT), JPEG, K-means clustering, Threshold value
Text-Image Separation in Document Images using Boundary/Perimeter DetectionIDES Editor
Document analysis plays an important role in office
automation, especially in intelligent signal processing. The
proposed system consists of two modules: block segmentation
and block identification. In this approach, first a document is
segmented into several non-overlapping blocks by utilizing a
novel recursive segmentation technique, and then extracts
the features embedded in each segmented block are extracted.
Two kinds of features, connected components and image
boundary/perimeter features are extracted. Document with
text inside image pose limitations in earlier reported literature.
This is taken care of by applying additional pass of the Run
Length Smearing on the extracted image that contains text.
Proposed scheme is independent of type and language of the
document.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
New Approach of Preprocessing For Numeral RecognitionIJERA Editor
The present paper proposes a new approach of preprocessing for handwritten, printed and isolated numeral
characters. The new approach reduces the size of the input image of each numeral by discarding the redundant
information. This method reduces also the number of features of the attribute vector provided by the extraction
features method. Numeral recognition is carried out in this work through k nearest neighbors and multilayer
perceptron techniques. The simulations have obtained a good rate of recognition in fewer running time.
OCR for Gujarati Numeral using Neural Networkijsrd.com
This papers functions within to reduce individuality popularity (OCR) program for hand-written Gujarati research. One can find so much of work for Indian own native different languages like Hindi, Gujarati, Tamil, Bengali, Malayalam, Gurumukhi etc., but Gujarati is a vocabulary for which hardly any work is traceable especially for hand-written individuals. Here in this work a nerve program is provided for Gujarati hand-written research popularity. This paper deals with an optical character recognition (OCR) system for handwritten Gujarati numbers. A several break up food ahead nerve program is suggested for variation of research. The functions of Gujarati research are abstracted by four different details of research. Reduction and skew- changes are also done for preprocessing of hand-written research before their variation. This work has purchased approximately 81% of performance for Gujarati handwritten numerals.
Quality Measurements of Lossy Image Steganography Based on H-AMBTC Technique ...AM Publications,India
Steganography is a type of image information concealing technique which hides a secret message in a different media such as image, video and audio etc, called cover file. The main idea of steganography is to provide security to private or public data. In this paper we combined among Hadamard transformation and Absolute Moment Block Truncation Coding to make a new concept called (H-AMBTC), this concept used for compressing the cover file and conceal the secret data into the cover file. The H-AMBTC compression is not only image compression, but it is more than the AMBTC technique as only half of the number of pixels in the binary converted image are transmitted. In this paper, the comparison process of the H-AMBTC technique is done for 2x2, 4x4, 8x8 and 16x16 block sizes. H-AMBTC is a lossy technique as the cover image and the secret image can be recovered completely.
Feature Extraction and Feature Selection using Textual Analysisvivatechijri
After pre-processing the images in character recognition systems, the images are segmented based on
certain characteristics known as “features”. The feature space identified for character recognition is however
ranging across a huge dimensionality. To solve this problem of dimensionality, the feature selection and feature
extraction methods are used. Hereby in this paper, we are going to discuss, the different techniques for feature
extraction and feature selection and how these techniques are used to reduce the dimensionality of feature space
to improve the performance of text categorization.
A new hybrid steganographic method for histogram preservation IJEEE
This paper presents a histogram preserving data embedding method for grey-scale images which is based on pixel value differencing (PVD) and least-significant-bit (LSB) substitution methods. Various PVD based steganographic methods achieve high data embedding capacity with minimum distortions in stego image at the cost of change in histogram characteristics which is can be detected by histogram based steganalysers. This persistent problem can been taken care off by proposed method of data hiding. The improved performance of the proposed method is verified through extensive simulations.
A systematic image compression in the combination of linear vector quantisati...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IEEE Final Year Projects 2011-2012 :: Elysium Technologies Pvt Ltd::Imageproc...sunda2011
IEEE Final Year Projects 2011-2012 :: Elysium Technologies Pvt Ltd
IEEE projects, final year projects, students project, be project, engineering projects, academic project, project center in madurai, trichy, chennai, kollam, coimbatore
Data Steganography for Optical Color Image CryptosystemsCSCJournals
In this paper, an optical color image cryptosystem with a data hiding scheme is proposed. In the proposed optical cryptosystem, a confidential color image is embedded into the host image of the same size. Then the stego-image is encrypted by using the double random phase encoding algorithm. The seeds to generate random phase data are hidden in the encrypted stego-image by a content-dependent and low distortion data embedding technique. The confidential image and secret data delivery is accomplished by hiding the image into the host image and embedding the data into the encrypted stego-image. Experimental results show that the proposed data steganographic cryptosystem provides large data hiding capacity and high reconstructed image quality.
WEB IMAGE RETRIEVAL USING CLUSTERING APPROACHEScscpconf
Image retrieval system is an active area to propose a new approach to retrieve images from the
large image database. In this concerned, we proposed an algorithm to represent images using
divisive based and partitioned based clustering approaches. The HSV color component and Haar wavelet transform is used to extract image features. These features are taken to segment an image to obtain objects. For segmenting an image, we used modified k-means clustering algorithm to group similar pixel together into K groups with cluster centers. To modify Kmeans, we proposed a divisive based clustering algorithm to determine the number of cluster and get back with number of cluster to k-means to obtain significant object groups. In addition, we also discussed the similarity distance measure using threshold value and object uniqueness to quantify the results.
Reconstructing the Path of the Object based on Time and Date OCR in Surveilla...ijtsrd
The inclusion of time based queries in video indexing application is enables by the recognition of time and date stamps in CCTV video. In this paper, we propose the system for reconstructing the path of the object in surveillance cameras based on time and date optical character recognition system. Since there is no boundary in region for time and date, Discrete Cosine Transform DCT method is applied in order to locate the region area. After the region for time and date is located, it is segmented and then features for the symbols of the time and date are extracted. Back propagation neural network is used for recognition of the features and then stores the result in the database. By using the resulted database, the system reconstructs the path for the object based on time. The proposed system will be implemented in MATLAB. Pyae Phyo Thu | Mie Mie Tin | Ei Phyu Win | Cho Thet Mon "Reconstructing the Path of the Object based on Time and Date OCR in Surveillance System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27981.pdfPaper URL: https://www.ijtsrd.com/home-science/education/27981/reconstructing-the-path-of-the-object-based-on-time-and-date-ocr-in-surveillance-system/pyae-phyo-thu
Faster Training Algorithms in Neural Network Based Approach For Handwritten T...CSCJournals
Handwritten text and character recognition is a challenging task compared to recognition of handwritten numeral and computer printed text due to its large variety in nature. As practical pattern recognition problems uses bulk data and there is a one step self sufficient deterministic theory to resolve recognition problems by calculating inverse of Hessian Matrix and multiplication the inverse matrix it with first order local gradient vector. But in practical cases when neural network is large the inversing operation of the Hessian Matrix is not manageable and another condition must be satisfied the Hessian Matrix must be positive definite which may not be satishfied. In these cases some repetitive recursive models are taken. In several research work in past decade it was experienced that Neural Network based approach provides most reliable performance in handwritten character and text recognition but recognition performance depends upon some important factors like no of training samples, reliable features and no of features per character, training time, variety of handwriting etc. Important features from different types of handwriting are collected and are fed to the neural network for training. It is true that more no of features increases test efficiency but it takes longer time to converge the error curve. To reduce this training time effectively proper train algorithm should be chosen so that the system provides best train and test efficiency in least possible time that is to provide the system fastest intelligence. We have used several second order conjugate gradient algorithms for training of neural network. We have found that Scaled Conjugate Gradient Algorithm , a second order training algorithm as the fastest for training of neural network for our application. Training using SCG takes minimum time with excellent test efficiency. A scanned handwritten text is taken as input and character level segmentation is done. Some important and reliable features from each character are extracted and used as input to a neural network for training. When the error level reaches into a satisfactory level (10 -12 ) weights are accepted for testing a test script. Finally a lexicon matching algorithm solves the minor misclassification problems.
Quality Measurements of Lossy Image Steganography Based on H-AMBTC Technique ...AM Publications,India
Steganography is a type of image information concealing technique which hides a secret message in a different media such as image, video and audio etc, called cover file. The main idea of steganography is to provide security to private or public data. In this paper we combined among Hadamard transformation and Absolute Moment Block Truncation Coding to make a new concept called (H-AMBTC), this concept used for compressing the cover file and conceal the secret data into the cover file. The H-AMBTC compression is not only image compression, but it is more than the AMBTC technique as only half of the number of pixels in the binary converted image are transmitted. In this paper, the comparison process of the H-AMBTC technique is done for 2x2, 4x4, 8x8 and 16x16 block sizes. H-AMBTC is a lossy technique as the cover image and the secret image can be recovered completely.
Feature Extraction and Feature Selection using Textual Analysisvivatechijri
After pre-processing the images in character recognition systems, the images are segmented based on
certain characteristics known as “features”. The feature space identified for character recognition is however
ranging across a huge dimensionality. To solve this problem of dimensionality, the feature selection and feature
extraction methods are used. Hereby in this paper, we are going to discuss, the different techniques for feature
extraction and feature selection and how these techniques are used to reduce the dimensionality of feature space
to improve the performance of text categorization.
A new hybrid steganographic method for histogram preservation IJEEE
This paper presents a histogram preserving data embedding method for grey-scale images which is based on pixel value differencing (PVD) and least-significant-bit (LSB) substitution methods. Various PVD based steganographic methods achieve high data embedding capacity with minimum distortions in stego image at the cost of change in histogram characteristics which is can be detected by histogram based steganalysers. This persistent problem can been taken care off by proposed method of data hiding. The improved performance of the proposed method is verified through extensive simulations.
A systematic image compression in the combination of linear vector quantisati...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IEEE Final Year Projects 2011-2012 :: Elysium Technologies Pvt Ltd::Imageproc...sunda2011
IEEE Final Year Projects 2011-2012 :: Elysium Technologies Pvt Ltd
IEEE projects, final year projects, students project, be project, engineering projects, academic project, project center in madurai, trichy, chennai, kollam, coimbatore
Data Steganography for Optical Color Image CryptosystemsCSCJournals
In this paper, an optical color image cryptosystem with a data hiding scheme is proposed. In the proposed optical cryptosystem, a confidential color image is embedded into the host image of the same size. Then the stego-image is encrypted by using the double random phase encoding algorithm. The seeds to generate random phase data are hidden in the encrypted stego-image by a content-dependent and low distortion data embedding technique. The confidential image and secret data delivery is accomplished by hiding the image into the host image and embedding the data into the encrypted stego-image. Experimental results show that the proposed data steganographic cryptosystem provides large data hiding capacity and high reconstructed image quality.
WEB IMAGE RETRIEVAL USING CLUSTERING APPROACHEScscpconf
Image retrieval system is an active area to propose a new approach to retrieve images from the
large image database. In this concerned, we proposed an algorithm to represent images using
divisive based and partitioned based clustering approaches. The HSV color component and Haar wavelet transform is used to extract image features. These features are taken to segment an image to obtain objects. For segmenting an image, we used modified k-means clustering algorithm to group similar pixel together into K groups with cluster centers. To modify Kmeans, we proposed a divisive based clustering algorithm to determine the number of cluster and get back with number of cluster to k-means to obtain significant object groups. In addition, we also discussed the similarity distance measure using threshold value and object uniqueness to quantify the results.
Reconstructing the Path of the Object based on Time and Date OCR in Surveilla...ijtsrd
The inclusion of time based queries in video indexing application is enables by the recognition of time and date stamps in CCTV video. In this paper, we propose the system for reconstructing the path of the object in surveillance cameras based on time and date optical character recognition system. Since there is no boundary in region for time and date, Discrete Cosine Transform DCT method is applied in order to locate the region area. After the region for time and date is located, it is segmented and then features for the symbols of the time and date are extracted. Back propagation neural network is used for recognition of the features and then stores the result in the database. By using the resulted database, the system reconstructs the path for the object based on time. The proposed system will be implemented in MATLAB. Pyae Phyo Thu | Mie Mie Tin | Ei Phyu Win | Cho Thet Mon "Reconstructing the Path of the Object based on Time and Date OCR in Surveillance System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27981.pdfPaper URL: https://www.ijtsrd.com/home-science/education/27981/reconstructing-the-path-of-the-object-based-on-time-and-date-ocr-in-surveillance-system/pyae-phyo-thu
Faster Training Algorithms in Neural Network Based Approach For Handwritten T...CSCJournals
Handwritten text and character recognition is a challenging task compared to recognition of handwritten numeral and computer printed text due to its large variety in nature. As practical pattern recognition problems uses bulk data and there is a one step self sufficient deterministic theory to resolve recognition problems by calculating inverse of Hessian Matrix and multiplication the inverse matrix it with first order local gradient vector. But in practical cases when neural network is large the inversing operation of the Hessian Matrix is not manageable and another condition must be satisfied the Hessian Matrix must be positive definite which may not be satishfied. In these cases some repetitive recursive models are taken. In several research work in past decade it was experienced that Neural Network based approach provides most reliable performance in handwritten character and text recognition but recognition performance depends upon some important factors like no of training samples, reliable features and no of features per character, training time, variety of handwriting etc. Important features from different types of handwriting are collected and are fed to the neural network for training. It is true that more no of features increases test efficiency but it takes longer time to converge the error curve. To reduce this training time effectively proper train algorithm should be chosen so that the system provides best train and test efficiency in least possible time that is to provide the system fastest intelligence. We have used several second order conjugate gradient algorithms for training of neural network. We have found that Scaled Conjugate Gradient Algorithm , a second order training algorithm as the fastest for training of neural network for our application. Training using SCG takes minimum time with excellent test efficiency. A scanned handwritten text is taken as input and character level segmentation is done. Some important and reliable features from each character are extracted and used as input to a neural network for training. When the error level reaches into a satisfactory level (10 -12 ) weights are accepted for testing a test script. Finally a lexicon matching algorithm solves the minor misclassification problems.
Numeral recognition is an important research direction in field of pattern recognition, and it has
broad application prospects. Aiming at four arithmetic operations of general printed formats, this article
adopts a multiple hybrid recognition method and is applied to automatically calculating. This method mainly
uses BP neural network and template matching method to distinguish the numerals and operators, in order
to increase the operation speed and recognition accuracy. Sample images of four arithmetic operations are
extracted from printed books, and they are used for testing the performance of proposed recognition
method. The experiments show that the method provides correct recognition rate of 96% and correct
calculation rate of 89%.
Segmentation and recognition of handwritten digit numeral string using a mult...ijfcstjournal
In this paper, the use of Multi-Layer Perceptron (MLP) Neural Network model is proposed for recognizing
unconstrained offline handwritten Numeral strings. The Numeral strings are segmented and isolated
numerals are obtained using a connected component labeling (CCL) algorithm approach. The structural
part of the models has been modeled using a Multilayer Perceptron Neural Network. This paper also
presents a new technique to remove slope and slant from handwritten numeral string and to normalize the
size of text images and classify with supervised learning methods. Experimental results on a database of
102 numeral string patterns written by 3 different people show that a recognition rate of 99.7% is obtained
on independent digits contained in the numeral string of digits includes both the skewed and slant data.
A Survey on Tamil Handwritten Character Recognition using OCR Techniquescscpconf
In today’s fast growing technology, digital recognitions are playing wide role and providing
more scope to perform research in OCR techniques. Recognition of Tamil handwritten scripts is
complicated compared to other western language scripts. However, many researchers have
provided real-time solutions for offline Tamil character recognition also. Offline Tamil
handwritten documents recognition still offers many motivating challenges to researchers.
Current research offers many solutions on Tamil handwritten documents recognition even then
reasonable accuracy and performance has not been achieved. This paper analyses the various approaches and challenges concerning offline Tamil handwritten character recognition
Offline Character Recognition Using Monte Carlo Method and Neural Networkijaia
Human Machine interface are constantly gaining improvements because of increasing development of
computer tools. Handwritten Character Recognition do have various significant applications like form
scanning, verification, validation, or checks reading. Because of the importance of these applications
passionate research in the field of Off-Line handwritten character recognition is going on. The challenge in
recognising the handwritings lies in the nature of humans, having unique styles in terms of font, contours,
etc. This paper presents a novice approach to identify the offline characters; we call it as character divider
approach which can be used after pre-processing stage. We devise an innovative approach for feature
extraction known as vector contour. We also discuss the pros and cons including limitations, of our
approach
PARALLEL GENERATION OF IMAGE LAYERS CONSTRUCTED BY EDGE DETECTION USING MESSA...ijcsit
Edge detection is one of the most fundamental algorithms in digital image processing. Many algorithms have been implemented to construct image layers extracted from the original image based on selecting threshold parameters. Changing theses parameters to get a high quality layer is time consuming. In this paper, we propose two parallel technique, NASHT1 and NASHT2, to generate multiple layers of an input
image automatically to enable the image tester to select the highest quality detected edges. In addition, the
effect of intensive I/O operations and the number of parallel running processes on the performance of the proposed techniques have also been studied.
IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of mechanical and civil engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in mechanical and civil engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
An effective approach to offline arabic handwriting recognitionijaia
Segmentation is the most challenging part of the Arabic handwriting recognition, due to the unique
characteristics of Arabic writing that allows the same shape to denote different characters. In this paper,
an off-line Arabic handwriting recognition system is proposed. The processing details are presented in
three main stages. Firstly, the image is skeletonized to one pixel thin. Secondly, transfer each diagonally
connected foreground pixel to the closest horizontal or vertical line. Finally, these orthogonal lines are
coded as vectors of unique integer numbers; each vector represents one letter of the word. In order to
evaluate the proposed techniques, the system has been tested on the IFN/ENIT database, and the
experimental results show that our method is superior to those methods currently available.
Bangla Optical Digits Recognition using Edge Detection MethodIOSR Journals
Abstract:This paper is based on Bangla Optical Digit Recognition (ODR) by the Edge detection technique. In this method, Bangla digit image converted into gray-scale which distributed by an M by N array form. Here input data are considered off-line printed digit’s image which collected from computer generated image, scanned documents or printed text. After addressing the gray-scale image against a variable in the form of an M by N array, where the value of array pointers are shown 255 for total white space, 0 (zero) for total dark space and value between 255 and 0 for mix of white and dark space of the image. At the next process, four edgestouch points as well as each touch point’s ratio use as parameters to determine each Bangla digit uniquely. Keywords-Edge, image,gray-scale, Matrix,ODR.
Tracking number plate from vehicle usingijfcstjournal
In Traffic surveillance, Tracking of the number plate from the vehicle is an important task, which demands
intelligent solution. In this document, extraction and Recognization of number plate from vehicles image
has been done using Matlab. It is assumed that images of the vehicle have been captured from Digital
Camera. Alphanumeric Characters on plate has been Extracted and recognized using template images of
alphanumeric characters.
This paper presents a new algorithm in MATLAB which has been used to extract the number plate from the
vehicle in various luminance conditions. Extracted image of the number plate can be seen in a text file for
verification purpose. Number plate identification is helpful in finding stolen cars, car parking management
system and identification of vehicle in traffic.
Similar to Hangul Recognition Using Support Vector Machine (20)
Text Mining in Digital Libraries using OKAPI BM25 ModelEditor IJCATR
The emergence of the internet has made vast amounts of information available and easily accessible online. As a result, most libraries have digitized their content in order to remain relevant to their users and to keep pace with the advancement of the internet. However, these digital libraries have been criticized for using inefficient information retrieval models that do not perform relevance ranking to the retrieved results. This paper proposed the use of OKAPI BM25 model in text mining so as means of improving relevance ranking of digital libraries. Okapi BM25 model was selected because it is a probability-based relevance ranking algorithm. A case study research was conducted and the model design was based on information retrieval processes. The performance of Boolean, vector space, and Okapi BM25 models was compared for data retrieval. Relevant ranked documents were retrieved and displayed at the OPAC framework search page. The results revealed that Okapi BM 25 outperformed Boolean model and Vector Space model. Therefore, this paper proposes the use of Okapi BM25 model to reward terms according to their relative frequencies in a document so as to improve the performance of text mining in digital libraries.
Green Computing, eco trends, climate change, e-waste and eco-friendlyEditor IJCATR
This study focused on the practice of using computing resources more efficiently while maintaining or increasing overall performance. Sustainable IT services require the integration of green computing practices such as power management, virtualization, improving cooling technology, recycling, electronic waste disposal, and optimization of the IT infrastructure to meet sustainability requirements. Studies have shown that costs of power utilized by IT departments can approach 50% of the overall energy costs for an organization. While there is an expectation that green IT should lower costs and the firm’s impact on the environment, there has been far less attention directed at understanding the strategic benefits of sustainable IT services in terms of the creation of customer value, business value and societal value. This paper provides a review of the literature on sustainable IT, key areas of focus, and identifies a core set of principles to guide sustainable IT service design.
Policies for Green Computing and E-Waste in NigeriaEditor IJCATR
Computers today are an integral part of individuals’ lives all around the world, but unfortunately these devices are toxic to the environment given the materials used, their limited battery life and technological obsolescence. Individuals are concerned about the hazardous materials ever present in computers, even if the importance of various attributes differs, and that a more environment -friendly attitude can be obtained through exposure to educational materials. In this paper, we aim to delineate the problem of e-waste in Nigeria and highlight a series of measures and the advantage they herald for our country and propose a series of action steps to develop in these areas further. It is possible for Nigeria to have an immediate economic stimulus and job creation while moving quickly to abide by the requirements of climate change legislation and energy efficiency directives. The costs of implementing energy efficiency and renewable energy measures are minimal as they are not cash expenditures but rather investments paid back by future, continuous energy savings.
Performance Evaluation of VANETs for Evaluating Node Stability in Dynamic Sce...Editor IJCATR
Vehicular ad hoc networks (VANETs) are a favorable area of exploration which empowers the interconnection amid the movable vehicles and between transportable units (vehicles) and road side units (RSU). In Vehicular Ad Hoc Networks (VANETs), mobile vehicles can be organized into assemblage to promote interconnection links. The assemblage arrangement according to dimensions and geographical extend has serious influence on attribute of interaction .Vehicular ad hoc networks (VANETs) are subclass of mobile Ad-hoc network involving more complex mobility patterns. Because of mobility the topology changes very frequently. This raises a number of technical challenges including the stability of the network .There is a need for assemblage configuration leading to more stable realistic network. The paper provides investigation of various simulation scenarios in which cluster using k-means algorithm are generated and their numbers are varied to find the more stable configuration in real scenario of road.
Optimum Location of DG Units Considering Operation ConditionsEditor IJCATR
The optimal sizing and placement of Distributed Generation units (DG) are becoming very attractive to researchers these days. In this paper a two stage approach has been used for allocation and sizing of DGs in distribution system with time varying load model. The strategic placement of DGs can help in reducing energy losses and improving voltage profile. The proposed work discusses time varying loads that can be useful for selecting the location and optimizing DG operation. The method has the potential to be used for integrating the available DGs by identifying the best locations in a power system. The proposed method has been demonstrated on 9-bus test system.
Analysis of Comparison of Fuzzy Knn, C4.5 Algorithm, and Naïve Bayes Classifi...Editor IJCATR
Early detection of diabetes mellitus (DM) can prevent or inhibit complication. There are several laboratory test that must be done to detect DM. The result of this laboratory test then converted into data training. Data training used in this study generated from UCI Pima Database with 6 attributes that were used to classify positive or negative diabetes. There are various classification methods that are commonly used, and in this study three of them were compared, which were fuzzy KNN, C4.5 algorithm and Naïve Bayes Classifier (NBC) with one identical case. The objective of this study was to create software to classify DM using tested methods and compared the three methods based on accuracy, precision, and recall. The results showed that the best method was Fuzzy KNN with average and maximum accuracy reached 96% and 98%, respectively. In second place, NBC method had respective average and maximum accuracy of 87.5% and 90%. Lastly, C4.5 algorithm had average and maximum accuracy of 79.5% and 86%, respectively.
Web Scraping for Estimating new Record from Source SiteEditor IJCATR
Study in the Competitive field of Intelligent, and studies in the field of Web Scraping, have a symbiotic relationship mutualism. In the information age today, the website serves as a main source. The research focus is on how to get data from websites and how to slow down the intensity of the download. The problem that arises is the website sources are autonomous so that vulnerable changes the structure of the content at any time. The next problem is the system intrusion detection snort installed on the server to detect bot crawler. So the researchers propose the use of the methods of Mining Data Records and the method of Exponential Smoothing so that adaptive to changes in the structure of the content and do a browse or fetch automatically follow the pattern of the occurrences of the news. The results of the tests, with the threshold 0.3 for MDR and similarity threshold score 0.65 for STM, using recall and precision values produce f-measure average 92.6%. While the results of the tests of the exponential estimation smoothing using ? = 0.5 produces MAE 18.2 datarecord duplicate. It slowed down to 3.6 datarecord from 21.8 datarecord results schedule download/fetch fix in an average time of occurrence news.
Evaluating Semantic Similarity between Biomedical Concepts/Classes through S...Editor IJCATR
Most of the existing semantic similarity measures that use ontology structure as their primary source can measure semantic similarity between concepts/classes using single ontology. The ontology-based semantic similarity techniques such as structure-based semantic similarity techniques (Path Length Measure, Wu and Palmer’s Measure, and Leacock and Chodorow’s measure), information content-based similarity techniques (Resnik’s measure, Lin’s measure), and biomedical domain ontology techniques (Al-Mubaid and Nguyen’s measure (SimDist)) were evaluated relative to human experts’ ratings, and compared on sets of concepts using the ICD-10 “V1.0” terminology within the UMLS. The experimental results validate the efficiency of the SemDist technique in single ontology, and demonstrate that SemDist semantic similarity techniques, compared with the existing techniques, gives the best overall results of correlation with experts’ ratings.
Semantic Similarity Measures between Terms in the Biomedical Domain within f...Editor IJCATR
The techniques and tests are tools used to define how measure the goodness of ontology or its resources. The similarity between biomedical classes/concepts is an important task for the biomedical information extraction and knowledge discovery. However, most of the semantic similarity techniques can be adopted to be used in the biomedical domain (UMLS). Many experiments have been conducted to check the applicability of these measures. In this paper, we investigate to measure semantic similarity between two terms within single ontology or multiple ontologies in ICD-10 “V1.0” as primary source, and compare my results to human experts score by correlation coefficient.
A Strategy for Improving the Performance of Small Files in Openstack Swift Editor IJCATR
This is an effective way to improve the storage access performance of small files in Openstack Swift by adding an aggregate storage module. Because Swift will lead to too much disk operation when querying metadata, the transfer performance of plenty of small files is low. In this paper, we propose an aggregated storage strategy (ASS), and implement it in Swift. ASS comprises two parts which include merge storage and index storage. At the first stage, ASS arranges the write request queue in chronological order, and then stores objects in volumes. These volumes are large files that are stored in Swift actually. During the short encounter time, the object-to-volume mapping information is stored in Key-Value store at the second stage. The experimental results show that the ASS can effectively improve Swift's small file transfer performance.
Integrated System for Vehicle Clearance and RegistrationEditor IJCATR
Efficient management and control of government's cash resources rely on government banking arrangements. Nigeria, like many low income countries, employed fragmented systems in handling government receipts and payments. Later in 2016, Nigeria implemented a unified structure as recommended by the IMF, where all government funds are collected in one account would reduce borrowing costs, extend credit and improve government's fiscal policy among other benefits to government. This situation motivated us to embark on this research to design and implement an integrated system for vehicle clearance and registration. This system complies with the new Treasury Single Account policy to enable proper interaction and collaboration among five different level agencies (NCS, FRSC, SBIR, VIO and NPF) saddled with vehicular administration and activities in Nigeria. Since the system is web based, Object Oriented Hypermedia Design Methodology (OOHDM) is used. Tools such as Php, JavaScript, css, html, AJAX and other web development technologies were used. The result is a web based system that gives proper information about a vehicle starting from the exact date of importation to registration and renewal of licensing. Vehicle owner information, custom duty information, plate number registration details, etc. will also be efficiently retrieved from the system by any of the agencies without contacting the other agency at any point in time. Also number plate will no longer be the only means of vehicle identification as it is presently the case in Nigeria, because the unified system will automatically generate and assigned a Unique Vehicle Identification Pin Number (UVIPN) on payment of duty in the system to the vehicle and the UVIPN will be linked to the various agencies in the management information system.
Assessment of the Efficiency of Customer Order Management System: A Case Stu...Editor IJCATR
The Supermarket Management System deals with the automation of buying and selling of good and services. It includes both sales and purchase of items. The project Supermarket Management System is to be developed with the objective of making the system reliable, easier, fast, and more informative.
Energy-Aware Routing in Wireless Sensor Network Using Modified Bi-Directional A*Editor IJCATR
Energy is a key component in the Wireless Sensor Network (WSN)[1]. The system will not be able to run according to its function without the availability of adequate power units. One of the characteristics of wireless sensor network is Limitation energy[2]. A lot of research has been done to develop strategies to overcome this problem. One of them is clustering technique. The popular clustering technique is Low Energy Adaptive Clustering Hierarchy (LEACH)[3]. In LEACH, clustering techniques are used to determine Cluster Head (CH), which will then be assigned to forward packets to Base Station (BS). In this research, we propose other clustering techniques, which utilize the Social Network Analysis approach theory of Betweeness Centrality (BC) which will then be implemented in the Setup phase. While in the Steady-State phase, one of the heuristic searching algorithms, Modified Bi-Directional A* (MBDA *) is implemented. The experiment was performed deploy 100 nodes statically in the 100x100 area, with one Base Station at coordinates (50,50). To find out the reliability of the system, the experiment to do in 5000 rounds. The performance of the designed routing protocol strategy will be tested based on network lifetime, throughput, and residual energy. The results show that BC-MBDA * is better than LEACH. This is influenced by the ways of working LEACH in determining the CH that is dynamic, which is always changing in every data transmission process. This will result in the use of energy, because they always doing any computation to determine CH in every transmission process. In contrast to BC-MBDA *, CH is statically determined, so it can decrease energy usage.
Security in Software Defined Networks (SDN): Challenges and Research Opportun...Editor IJCATR
In networks, the rapidly changing traffic patterns of search engines, Internet of Things (IoT) devices, Big Data and data centers has thrown up new challenges for legacy; existing networks; and prompted the need for a more intelligent and innovative way to dynamically manage traffic and allocate limited network resources. Software Defined Network (SDN) which decouples the control plane from the data plane through network vitalizations aims to address these challenges. This paper has explored the SDN architecture and its implementation with the OpenFlow protocol. It has also assessed some of its benefits over traditional network architectures, security concerns and how it can be addressed in future research and related works in emerging economies such as Nigeria.
Measure the Similarity of Complaint Document Using Cosine Similarity Based on...Editor IJCATR
Report handling on "LAPOR!" (Laporan, Aspirasi dan Pengaduan Online Rakyat) system depending on the system administrator who manually reads every incoming report [3]. Read manually can lead to errors in handling complaints [4] if the data flow is huge and grows rapidly, it needs at least three days to prepare a confirmation and it sensitive to inconsistencies [3]. In this study, the authors propose a model that can measure the identities of the Query (Incoming) with Document (Archive). The authors employed Class-Based Indexing term weighting scheme, and Cosine Similarities to analyse document similarities. CoSimTFIDF, CoSimTFICF and CoSimTFIDFICF values used in classification as feature for K-Nearest Neighbour (K-NN) classifier. The optimum result evaluation is pre-processing employ 75% of training data ratio and 25% of test data with CoSimTFIDF feature. It deliver a high accuracy 84%. The k = 5 value obtain high accuracy 84.12%
Application of 3D Printing in EducationEditor IJCATR
This paper provides a review of literature concerning the application of 3D printing in the education system. The review identifies that 3D Printing is being applied across the Educational levels [1] as well as in Libraries, Laboratories, and Distance education systems. The review also finds that 3D Printing is being used to teach both students and trainers about 3D Printing and to develop 3D Printing skills.
Survey on Energy-Efficient Routing Algorithms for Underwater Wireless Sensor ...Editor IJCATR
In underwater environment, for retrieval of information the routing mechanism is used. In routing mechanism there are three to four types of nodes are used, one is sink node which is deployed on the water surface and can collect the information, courier/super/AUV or dolphin powerful nodes are deployed in the middle of the water for forwarding the packets, ordinary nodes are also forwarder nodes which can be deployed from bottom to surface of the water and source nodes are deployed at the seabed which can extract the valuable information from the bottom of the sea. In underwater environment the battery power of the nodes is limited and that power can be enhanced through better selection of the routing algorithm. This paper focuses the energy-efficient routing algorithms for their routing mechanisms to prolong the battery power of the nodes. This paper also focuses the performance analysis of the energy-efficient algorithms under which we can examine the better performance of the route selection mechanism which can prolong the battery power of the node
Comparative analysis on Void Node Removal Routing algorithms for Underwater W...Editor IJCATR
The designing of routing algorithms faces many challenges in underwater environment like: propagation delay, acoustic channel behaviour, limited bandwidth, high bit error rate, limited battery power, underwater pressure, node mobility, localization 3D deployment, and underwater obstacles (voids). This paper focuses the underwater voids which affects the overall performance of the entire network. The majority of the researchers have used the better approaches for removal of voids through alternate path selection mechanism but still research needs improvement. This paper also focuses the architecture and its operation through merits and demerits of the existing algorithms. This research article further focuses the analytical method of the performance analysis of existing algorithms through which we found the better approach for removal of voids
Decay Property for Solutions to Plate Type Equations with Variable CoefficientsEditor IJCATR
In this paper we consider the initial value problem for a plate type equation with variable coefficients and memory in
1 n R n ), which is of regularity-loss property. By using spectrally resolution, we study the pointwise estimates in the spectral
space of the fundamental solution to the corresponding linear problem. Appealing to this pointwise estimates, we obtain the global
existence and the decay estimates of solutions to the semilinear problem by employing the fixed point theorem
Prediction of Heart Disease in Diabetic patients using Naive Bayes Classifica...Editor IJCATR
The objective of our paper is to predict the risk of heart disease in diabetic patients. In this research paper we are applying Naive Bayes data mining classification technique which is a probabilistic classifier based on Bayes theorem with strong (naive) independence assumptions between the features. Data mining techniques have been widely used in health care systems for prediction of various diseases with accuracy. Health care industry contains large amount of data and hidden information. Effective decisions are made with this hidden information by applying data mining techniques. These techniques are used to discover hidden patterns and relationships from the datasets. The major challenge facing the healthcare industry is the provision for quality services at affordable costs. A quality service implies diagnosing patients correctly and treating them effectively. In this proposed system certain attributes are consider in diabetic patients to predict the risk of heart disease
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
Hangul Recognition Using Support Vector Machine
1. International Journal of Computer Applications Technology and Research
Volume 7–Issue 07, 281-285, 2018, ISSN:-2319–8656
www.ijcat.com 281
Hangul Recognition Using Support Vector Machine
Rahmatina Hidayati
Department of Electrical Engineering
University of Brawijaya
Malang, East Java, Indonesia
Moechammad Sarosa
Department of Electrical Engineering
State Polytechnic of Malang
Malang, East Java, Indonesia
Panca Mudjirahardjo
Department of Electrical Engineering
University of Brawijaya
Malang, East Java, Indonesia
Abstract: The recognition of Hangul Image is more difficult compared with that of Latin. It could be recognized from the structural
arrangement. Hangul is arranged from two dimensions while Latin is only from the left to the right. The current research creates a
system to convert Hangul image into Latin text in order to use it as a learning material on reading Hangul. In general, image
recognition system is divided into three steps. The first step is preprocessing, which includes binarization, segmentation through
connected component-labeling method, and thinning with Zhang Suen to decrease some pattern information. The second is receiving
the feature from every single image, whose identification process is done through chain code method. The third is recognizing the
process using Support Vector Machine (SVM) with some kernels. It works through letter image and Hangul word recognition. It
consists of 34 letters, each of which has 15 different patterns. The whole patterns are 510, divided into 3 data scenarios. The highest
result achieved is 94,7% using SVM kernel polynomial and radial basis function. The level of recognition result is influenced by many
trained data. Whilst the recognition process of Hangul word applies to the type 2 Hangul word with 6 different patterns. The difference
of these patterns appears from the change of the font type. The chosen fonts for data training are such as Batang, Dotum, Gaeul,
Gulim, Malgun Gothic. Arial Unicode MS is used to test the data. The lowest accuracy is achieved through the use of SVM kernel
radial basis function, which is 69%. The same result, 72 %, is given by the SVM kernel linear and polynomial.
Keywords: Support Vector Machine; SVM; Kernel Polynomial; Kernel Linear; Kernel Radial Basis Function; Hangul
1. INTRODUCTION
Optical Character Recognition (OCR) is a character
introduction system with images input. It contains texts that
would be converted to the edited versions[1]. The work of
OCR system depends on the kind of processed text.
Generally, the text is divided into three categories. They are
written, printed, and typed text[2].
Some researches on OCR System have been conducted.
One of methods ever used is Support Vector Machine (SVM).
A kind of character which had ever been searched by using
SVM is Hindi number, which is known as Numeral Kanada,
upper case and lower case alphabet A-Z [2,3,4]. The SVM
method is used with different data, Korean characters known
as Hangul.
Hangul recognition is more difficult compared with Latin
due to its complicated arrangement. Hangul is arranged from
2 dimensions (both left and right side), while Latin is arranged
from left to the right [5].
A Research on Hangul recognition has ever been
conducted, where the writer applies the Stochastic
Relationship Modeling to the recognition process of Hangul
syllable writing. The output of the research is Hangul syllable
texts[6].
So far, the research on Hangul recognition is conducted
with Hangul texts output. The current research will improve
the image conversion of Hangul with Latin text output. The
image of Hangul converted into Latin text can be used as a
learning material on how to read Hangul.
OCR system, in general, is divided into three steps. They
are preprocessing, feature extraction, and recognition. Pre-
process includes three stages: binarization to change the
grayscale image into black white; segmentation, which is
processed through connected component labeling, to separate
the input into individual word; and thinning to decrease some
information pattern (thin Line) in order to be easily analyzed
[7]. The research will employ algorithm Zhang Suen, which
works faster than the other thinning algorithms[8].
The next step, after pre-process, is feature extraction. It
has an important role on recognition process. It works through
generating the basic component of the image called
features[9]. The feature extraction used in the current research
is chain code. The last process is recognition, using the SVM
method with some kernels (linear, polynomial, and radial
basis function).
2. METHODOLOGY
Generally, OCR system is divided into three main steps.
They are preprocessing (binarization, segmentation, and
thinning), feature extraction in which in this research uses
chain code, and recognition by applying Support Vector
Machine (SVM) method. Figure 1 shows the general process
of Hangul recognition.
Hangul Image
Figure 1. Block diagram of Hangul recognition
The input image used in the current research is the letter
and Hangul word. The letter consists of 21 vowels and 13
consonants, shown in Figure 2 with Latin letter. Each letter
has 15 different forms. The whole data are amounted to 510.
Preprocessing
Feature Extraction
Hangul Recognition
2. International Journal of Computer Applications Technology and Research
Volume 7–Issue 07, 281-285, 2018, ISSN:-2319–8656
www.ijcat.com 282
Figure 2. The Letters of Hangul and Latin[10]
Meanwhile for word, there are 6 ways on how to arrange
the letter of Hangul into word. The first type is shown in
Figure 3[10]. The discussion focuses on data type 2.
‘
Figure 3. 6 the ways to arrange the letter of Hangul[10]
Meanwhile, the example of type 2 Hangul word is shown
in Figure 4. Each word consists of 6 different forms. They are
achieved by changing the word font. The used fonts are Arial,
Batang, Dotum, Gaeul, Gulim, and Malgun Gothic.
Figure 4. The example of Hangul word
2.1 Preprocessing
The preprocessing includes 3 steps. First, the binarization
or thresholding, is implemented to change the grayscale image
become black white. The process of thresholding will produce
the binary image, the image which has two steps of grayish
(black and white). Generally, the process of floating the
grayscale image to produce the biner image are as follows[11]:
(1)
With g (x,y) is the binary image from grayscale image f
(x,y) and T assert the percentage of threshold.
Second, thinning is used to decrease some information to
a pattern becomes thin line in order to be easy to analyzed[7].
In this case, it will be applied the Zhang Suen algorithm
which has faster performance compare with the other thinning
algorithm[8]. To process thinning algorithm is shown in the
Figure 6. This algorithm uses the pixel 3x3 and 8 degrees as
in the Figure 5. P1 is a pixel that will be checked, if it fulfills
the fixed condition, so the pixel will be deleted. The
conditions are as follows[12]:
(a) 2 ≤ B(P1) ≤ 6 (2)
(b) A(P1) = 1 (3)
(c) P2 x P4 x P6 = 0, and (4)
(d) P4 x P6 x P8 = 0 (5)
(e) P2 x P4 x P8 = 0, and (6)
(f) P2 x P6 x P8 = 0 (7)
Figure 5. The pixel 3x3 with 8 degrees
3. International Journal of Computer Applications Technology and Research
Volume 7–Issue 07, 281-285, 2018, ISSN:-2319–8656
www.ijcat.com 283
Start
P2 x P4 x P8 = 0 &
P2 x P6 x P8 = 0 ?
End
2 ≤ B(P1) ≤ 6 &
A(P1) = 1 ?
Delete pixel
Delete pixel
P2 x P4 x P6 = 0 &
P4 x P6 x P8 = 0 ?
Delete pixel
Matrix of
thinning result
Tidak
Tidak
Tidak
Ya
Ya
Ya
Scan pixel
Figure 6. The Diagram algorithm of Zhang Suen
2.2 Feature Extraction
The next step after preprocessing is feature extraction,
which has an important role on recognition. This process will
generate the necessary component of an image called
features[9]. The used feature extraction is chain code which
functions as the direction search. The direction usually uses
the following regulation Figure 7.
3 2 1
4 0
5 6 7
Figure 7. The direction of sequence code with 8 degrees[13]
The sequence code is made through checking the
direction of a pixel connected to the other pixels with 8
degrees. Each direction has different number. The pointed
sign shows the first pixel. It is a place where the next steps
will be fixed[13]. Figure 8 shows letter B with its sequence
code.
Figure 8. The direction of the sequence code in letter B
In order to be processed into SVM, the feature extraction
must have the same amount of features. Therefore,
normalization needs to be done. It also aims to decrease the
amount of feature which reoccurs. The normalization process
for chain code can be done with the following pattern[12]:
(8)
Note:
N = the amount of feature wanted
= the amount of feature normalized
= the amount of all letters normalized
2.3 Support Vector Machine (SVM)
The Support Vector Machine (SVM) is found in 1992 by
Boser, Guyon, and Vapnik. The basic concept is the
combination of computation theories introduced in previous
years, such as the margin hyperplane and kernel. The concept
of SVM can be seen as an effort to look for the best
hyperplane to separate two classes in the input grade.
Figure 9 shows some data of the two class member (+1
and -1), where (a) shows some alternative separated line
(Discrimination Boundaries), and (b) shows the best
hyperplane. The best hyperplane can be found by measuring
the distance between the hyperplane and the nearer data
known as margin [13]. The data in the margin is called
support vector[14].
Figure 9. (a) The alternative separated field, (b) The best
separated field with the biggest margin[14]
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Practically, the real data does not only consist of two
classes and they cannot be separated linearly. To solve this, an
approach needs to be conducted so that SVM is able to
classify the data input with N-Dimension or multi class, one
of which is one against one[14]. Besides, to arrange the data
input into higher dimension feature space, a function called
kernel is needed. Table 1 shows some kernels used in SVM
[15], and Figure 10 shows the process of recognition with
SVM.
Table 1. Kernel function in SVM[16]
Kernel Fungsi
Linear K(x,y) = x,y
Polynomial K(x,y) = (ᵞx.y+r)d
Radial Basis Function K(x,y) = exp(-ᵞ||x-y||2
, ᵞ>0
ϒ, r, and d are kernel parameter
Start
Testing data
image
Multiclass SVM recognition
Recognition result
Kernel accuracy
End
Chain code features
Figure 10. The diagram of Hangul recognition line with
Multiclass Support Vector Machine
3. EXPERIMENT RESULT
Algorithm line Zhang Suen in Figure 6 shows that slight
result is produced such as in Figure 11 (b).
Figure 11. (a) Binary image, (b) Letter CH after thinning
After achieving the slight feature, the system takes it in
accordance with the direction search in Figure 7. It generates
the features of CH letter as follow:
0;0;0;0;0;0;0;0;0;0;0;5;6;6;6;6;6;6;6;6;6;6;6;6;6;6;6;6;6;5;4;4;
4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;4;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;5;6;6;6;6;6;
6;6;6;6;6;6;6;6;6;6;6;6;5;. . . . ;CH;
If the feature is normalized according to the pattern (8), it
has the same amount as the minimal feature from input image.
Then, it will generate the following normalization feature:
0;0;0;0;0;0;0;0;5;6;6;6;6;6;6;6;6;6;6;6;6;6;5;4;4;4;4;4;4;4;4;4;
4;4;4;4;4;4;4;4;4;4;4;4;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;
0;0;0;0;5;6;6;6;6;6;6;6;6;6;6;6;6;6;5;. . . . ;CH;
After getting the feature, system will do the recognition
process. The letter recognition consists of 34 letters; each of
them formulates 15 forms. So, they are 540 in total. The data
scenario is shown in Table 2.
Table 2. Data scenario of Hangul letter recognition
Data Scenario Training Data Testing Data
DS1 170 (data A) 170 (data C)
DS2 340 (data A+B) 170 (data C)
DS3 510 (data A+B+C) 170 (data C)
Data testing process for DS1 and DS2 uses new data which
have not been tested before while that for DS3 uses the tested
ones.
Accuracy result of Hangul letter recognition for every
kernel is shown in Table 3.
Table 3. Accuracy result of Hangul letter recognition
Kernel SVM DS1 DS2 DS3
Linear 88,82% 94,11% 100%
Polynomial 89,41% 94,7% 100%
RBF 89,41% 94,7% 100%
Recognition mistake often occurs to the letter which has
the same form, such as 우 (U) with 유(YU) or the other way
around. Another letter which looks similar is 의(UI) with 위
(WI). The system output of Hangul letter is shown in Figure
12.
Figure 12. The result of Hangul letter recognition
In Hangul word recognition, researcher uses the form 2,
where the training data are 195 and the testing data are 39.
The accuracy for every kernel is shown in Table 4.(a) (b)
5. International Journal of Computer Applications Technology and Research
Volume 7–Issue 07, 281-285, 2018, ISSN:-2319–8656
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Table 4. Accuracy of Hangul word recognition
Kernel SVM Accuracy
Linear 72%
Polynomial 72%
RBF 69%
Output from the recognition of Hangul word type 2 is
shown in Figure 13. Recognition mistake occurs in the word
which has almost similar form, such as 쵸 (CHYO) with 초
(CHO).
Figure 13. The recognition result of Hangul word type 2
4. CONCLUSIONS
The research concludes that the more the trained data, the
higher the degree of accuracy. However, it needs to be
reexamined until the fixed number of data which give the
highest accuracy with SVM method is found.
In letter recognition process, kernel polynomial and RBF
achieve the highest accuracy of 94,7% in data scenario 2
(DS2). On the other hand, linear process gives the lowest
accuracy, 88,82%, in letter recognition, and RBF in Hangul
word with 69%.
5. FUTURE WORK
The future research might employ the feature from the
image with another method, while in the recognition process,
the researcher can use SVM method with different kernel.
Hangul recognition into Latin form may also be improved by
adding the meaning of the trained word.
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