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.
Image to Text Converter PPT. PPT contains step by step algorithms/methods to which we can convert images in to text , specially contains algorithms for images which contains human handwritting, can convert writting in to text, img to text.
Comparative study of two methods for Handwritten Devanagari Numeral RecognitionIOSR Journals
Abstract : In this paper two different methods for Numeral Recognition are proposed and their results are
compared. The objective of this paper is to provide an efficient and reliable method for recognition of
handwritten numerals. First method employs Grid based feature extraction and recognition algorithm. In this
method the features of the image are extracted by using grid technique and this feature set is then compared
with the feature set of database image for classification. While second method contains Image Centroid Zone
and Zone Centroid Zone algorithms for feature extraction and the features are applied to Artificial Neural
Network for recognition of input image. Machine text recognition is important research area because of its
applications in many areas like Bank, Post office, Hospitals etc.
Keywords: Handwritten Numeral Recognition, Grid Technique, ANN, Feature Extraction, Classification.
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.
With so much of our lives computerized, it is vitally important that machines and humans can understand one another and pass information back and forth. Mostly computers have things their way we have to & talk to them through relatively crude devices such as keyboards and mice so they can figure out what we want them to do. However, when it comes to processing more human kinds of information, like an old-fashioned printed book or a letter scribbled with a fountain pen, computers have to work much harder. That is where optical character recognition (OCR) comes in. Here we process the image, where we apply various pre-processing techniques like desk wing, binarization etc. and algorithms like Tesseract to recognize the characters and give us the final document. T.Gnana Prakash | K. Anusha"Text Extraction from Image using Python" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-6 , October 2017, URL: http://www.ijtsrd.com/papers/ijtsrd2501.pdf http://www.ijtsrd.com/computer-science/simulation/2501/text-extraction-from-image-using-python/tgnana-prakash
Image to Text Converter PPT. PPT contains step by step algorithms/methods to which we can convert images in to text , specially contains algorithms for images which contains human handwritting, can convert writting in to text, img to text.
Comparative study of two methods for Handwritten Devanagari Numeral RecognitionIOSR Journals
Abstract : In this paper two different methods for Numeral Recognition are proposed and their results are
compared. The objective of this paper is to provide an efficient and reliable method for recognition of
handwritten numerals. First method employs Grid based feature extraction and recognition algorithm. In this
method the features of the image are extracted by using grid technique and this feature set is then compared
with the feature set of database image for classification. While second method contains Image Centroid Zone
and Zone Centroid Zone algorithms for feature extraction and the features are applied to Artificial Neural
Network for recognition of input image. Machine text recognition is important research area because of its
applications in many areas like Bank, Post office, Hospitals etc.
Keywords: Handwritten Numeral Recognition, Grid Technique, ANN, Feature Extraction, Classification.
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.
With so much of our lives computerized, it is vitally important that machines and humans can understand one another and pass information back and forth. Mostly computers have things their way we have to & talk to them through relatively crude devices such as keyboards and mice so they can figure out what we want them to do. However, when it comes to processing more human kinds of information, like an old-fashioned printed book or a letter scribbled with a fountain pen, computers have to work much harder. That is where optical character recognition (OCR) comes in. Here we process the image, where we apply various pre-processing techniques like desk wing, binarization etc. and algorithms like Tesseract to recognize the characters and give us the final document. T.Gnana Prakash | K. Anusha"Text Extraction from Image using Python" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-6 , October 2017, URL: http://www.ijtsrd.com/papers/ijtsrd2501.pdf http://www.ijtsrd.com/computer-science/simulation/2501/text-extraction-from-image-using-python/tgnana-prakash
Optical character recognition, usually abbreviated to OCR, is the mechanical or electronic conversion of scanned images of handwritten, typewritten or printed text into machine-encoded text.
It is a system that provides a full alphanumeric recognition of printed or handwritten characters at electronic speed by simply scanning the form. It is widely used as a form of data entry from some sort of original paper data source, whether documents, sales receipts, mail, or any number of printed records.
It is a common method of digitizing printed texts so that they can be electronically searched, stored more compactly, displayed on-line, and used in machine processes such as machine translation, text-to-speech and text mining.OCR is a field of research in pattern recognition, artificial intelligence and computer vision. More recently, the term Intelligent Character Recognition(ICR) has been used to describe the process of interpreting image data, in particular alphanumeric text .
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
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.
An effective RGB color selection for complex 3D object structure in scene gra...IJECEIAES
Our goal of the project is to develop a complete, fully detailed 3D interactive model of the human body and systems in the human body, and allow the user to interacts in 3D with all the elements of that system, to teach students about human anatomy. Some organs, which contain a lot of details about a particular anatomy, need to be accurately and fully described in minute detail, such as the brain, lungs, liver and heart. These organs are need have all the detailed descriptions of the medical information needed to learn how to do surgery on them, and should allow the user to add careful and precise marking to indicate the operative landmarks on the surgery location. Adding so many different items of information is challenging when the area to which the information needs to be attached is very detailed and overlaps with all kinds of other medical information related to the area. Existing methods to tag areas was not allowing us sufficient locations to attach the information to. Our solution combines a variety of tagging methods, which use the marking method by selecting the RGB color area that is drawn in the texture, on the complex 3D object structure. Then, it relies on those RGB color codes to tag IDs and create relational tables that store the related information about the specific areas of the anatomy. With this method of marking, it is possible to use the entire set of color values (R, G, B) to identify a set of anatomic regions, and this also makes it possible to define multiple overlapping regions.
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%.
An Intelligent Skin Color Detection Method based on Fuzzy C-Means with Big Da...CrimsonpublishersTTEFT
An Intelligent Skin Color Detection Method based on Fuzzy C-Means with Big Data by Chih Huang Yen in Trends in Textile Engineering & Fashion Technology
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
In image processing colour segmentation is used to extract features of an object in both special and frequency domains. The objective of this paper is to use colour segmentation technique to identify the defected region of fruits and corresponding percentage of frequency components from its Spectrogram. Here we separate the defective portion of fruit using colour segmentation technique taking four images from four directions to get the appropriate result of 3D images. The percentage of the defective portion is determined using scatterplot of the colours of the image. Next, we apply the similar concept to spectrogram of an image (even applicable in speech signal) to extract the percentages of frequency components of the signal.
A comparative study on content based image retrieval methodsIJLT EMAS
Content-based image retrieval (CBIR) is a method of
finding images from a huge image database according to persons’
interests. Content-based here means that the search involves
analysis the actual content present in the image. As database of
images is growing daybyday, researchers/scholars are searching
for better techniques for retrieval of images maintaining good
efficiency. This paper presents the visual features and various
ways for image retrieval from the huge image database.
An Effective Method to Hide Texts Using Bit Plane Extractioniosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Optical character recognition, usually abbreviated to OCR, is the mechanical or electronic conversion of scanned images of handwritten, typewritten or printed text into machine-encoded text.
It is a system that provides a full alphanumeric recognition of printed or handwritten characters at electronic speed by simply scanning the form. It is widely used as a form of data entry from some sort of original paper data source, whether documents, sales receipts, mail, or any number of printed records.
It is a common method of digitizing printed texts so that they can be electronically searched, stored more compactly, displayed on-line, and used in machine processes such as machine translation, text-to-speech and text mining.OCR is a field of research in pattern recognition, artificial intelligence and computer vision. More recently, the term Intelligent Character Recognition(ICR) has been used to describe the process of interpreting image data, in particular alphanumeric text .
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
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.
An effective RGB color selection for complex 3D object structure in scene gra...IJECEIAES
Our goal of the project is to develop a complete, fully detailed 3D interactive model of the human body and systems in the human body, and allow the user to interacts in 3D with all the elements of that system, to teach students about human anatomy. Some organs, which contain a lot of details about a particular anatomy, need to be accurately and fully described in minute detail, such as the brain, lungs, liver and heart. These organs are need have all the detailed descriptions of the medical information needed to learn how to do surgery on them, and should allow the user to add careful and precise marking to indicate the operative landmarks on the surgery location. Adding so many different items of information is challenging when the area to which the information needs to be attached is very detailed and overlaps with all kinds of other medical information related to the area. Existing methods to tag areas was not allowing us sufficient locations to attach the information to. Our solution combines a variety of tagging methods, which use the marking method by selecting the RGB color area that is drawn in the texture, on the complex 3D object structure. Then, it relies on those RGB color codes to tag IDs and create relational tables that store the related information about the specific areas of the anatomy. With this method of marking, it is possible to use the entire set of color values (R, G, B) to identify a set of anatomic regions, and this also makes it possible to define multiple overlapping regions.
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%.
An Intelligent Skin Color Detection Method based on Fuzzy C-Means with Big Da...CrimsonpublishersTTEFT
An Intelligent Skin Color Detection Method based on Fuzzy C-Means with Big Data by Chih Huang Yen in Trends in Textile Engineering & Fashion Technology
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
In image processing colour segmentation is used to extract features of an object in both special and frequency domains. The objective of this paper is to use colour segmentation technique to identify the defected region of fruits and corresponding percentage of frequency components from its Spectrogram. Here we separate the defective portion of fruit using colour segmentation technique taking four images from four directions to get the appropriate result of 3D images. The percentage of the defective portion is determined using scatterplot of the colours of the image. Next, we apply the similar concept to spectrogram of an image (even applicable in speech signal) to extract the percentages of frequency components of the signal.
A comparative study on content based image retrieval methodsIJLT EMAS
Content-based image retrieval (CBIR) is a method of
finding images from a huge image database according to persons’
interests. Content-based here means that the search involves
analysis the actual content present in the image. As database of
images is growing daybyday, researchers/scholars are searching
for better techniques for retrieval of images maintaining good
efficiency. This paper presents the visual features and various
ways for image retrieval from the huge image database.
An Effective Method to Hide Texts Using Bit Plane Extractioniosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Old wine in new wineskins: Revisiting counselling in traditional Ndebele and ...IOSR Journals
The institution of counselling is present in all human communities as people share their sorrows,
mentor, empower and advise each other. The service of advising and grooming is all that counselling is. This
paper seeks to explore the institution of counselling in Shona and Ndebele traditional societies before the advent
of western formalised counselling institutions. The research sets to prove that counselling is not a new
phenomenon in these societies, that is a remnant of colonialism but rather it is an old institution that has been
window dressed with western strategies and formalisms. African traditional counselling strategies as seen in the
Shona and Ndebele examples emphasise more on the preventive forms of counselling than crisis counselling.
Advice and mentoring are prioritised in these societies as a way of helping people stay out of trouble that in
future will require therapeutic or crisis counselling. Modern day counselling has been professionalised and
commercialised and requires people to pay for it yet in Shona and Ndebele traditional societies it was part of
one’s responsibility to make sure others are well advised and counselled if they are emotionally troubled.
Professional counselling in marriage, carrier guidance, teenage grooming for example is not a new practice but
an old practice done differently like old wine in new wineskins.
Analysis of Multimedia Traffic Performance in a Multi-Class traffic environme...IOSR Journals
Abstract: The computer networks have evolved themselves into an altogether new generation with Mobile Ad-Hoc networks. The Mobile Ad-Hoc Networks are increasingly becoming more sophisticated and complex in terms of topology, routing and security[1][2][3]The new age MANETs incorporate routing of heavier traffic classes like audio, video and multimedia. It has become important to study the performance characteristics of the multimedia traffic class in MANETS [10] that includes packet loss rate and throughput. In this paper we will discuss these performance parameter throughput under different scenarios like varying Bandwidth, channel error rate, delay and fragment size. Keywords: MANET, Packet loss rate, Throughput, Bandwidth, Fragment size
Capacity Spectrum Method for RC Building with Cracked and Uncracked SectionIOSR Journals
one of the most widespread procedures for the assessment of building behavior, due to earthquake, is the Capacity Spectrum Method (CSM). In the scope of this procedure, capacity of the structure compares with the demands of earthquake ground motion on the structure. The capacity of the structure is represented by a nonlinear force-displacement curve, referred to as a pushover curve. The base shear forces and roof displacements are converted to equivalent spectral accelerations and spectral displacements, respectively, by means of coefficients that represent effective modal masses and modal participation factors. These spectral values define the capacity spectrum. The demands of the earthquake ground motion are represented by response spectra. A graphical construction that includes both capacity and demand spectra, results in an intersection of the two curves that estimates the performance of the structure to the earthquake. In this study, for determination of the performance levels, G+10 R.C.C. Building with cracked and uncracked section were taken. The structural Capacity of cracked and uncracked section compared with performance point value, which shows the structural capacity of building having cracked section is lesser than the uncracked section. Different modeling issues were analyzed to study the effect on Capacity of the structure with cracked and uncracked section for different position of Shear wall.
Nuclear Magnetic Resonance (NMR) Analysis of D - (+) - Glucose: A Guide to Sp...IOSR Journals
NMR spectroscopy has a wide range of applications including exchange phenomena, the
identification and structural studies of complex biomolecules. 1D 1H-NMR without water suppression, 1D
Carbon, 1D 13C-DEPT135, 2D Cosy, 2D HSQC, 2D TOCSY, 2D HMQC, and 2D HMBC techniques were used
to completely elucidate the structure of glucose with spectral induced at 400MHz.. The spectral were analysed
using spinworks 3. The results obtained from the spectral data were systematically combined to elucidate the
structure of the D-glucose. Full characterisation of D-glucose was achieved by assigning 1H and 13C signals,
starting from the known to unknown signals.
Exact Analytical Expression for Outgoing Intensity from the Top of the Atmosp...IOSR Journals
This research is a part of the work devoted on the application of analytical Discrete Ordinate (ADO) method to the polarized monochromatic radiative transfer equation undergoing anisotropic scattering with source function matrix in a finite coupled Atmosphere –Ocean media having flat interface boundary conditions involving specular reflection and transmission matrix. Discontinuities in the derivatives of the Stokes vector with respect to the cosine of the polar angle at smooth interface between the two media with different refractive indices (air and water) is tackled by using a suitable quadrature scheme devised earlier. Atmosphere and ocean are assumed to be homogeneous. No stratification is adopted in the two media. Exact expression for the
emergent radiation intensity vector from the top of the atmosphere is derived. Exact expressions for the emergent polarized radiation intensity vector from the air-water interface as well as from any point of the two medium in any direction can also be derived in terms of eigenvectors and eigenvalues.
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.
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.
With India growing it has made the ownership of vehicles a necessity. This has resulted in an civic problem. Parking areas have become congested due to the growing numbers of vehicles. The Number Plate Recognition System (NPR) plays an important role in different application as it is from parking to monitoring urban traffic and tracking automobile thefts. There are various NPR systems available today which work with different methodologies. In this paper, we attempt to review the various techniques and their usage. The NPR system has been implemented using template Matching and its accuracy was found to be 90.2% for number plates
License Plate Recognition using Morphological Operation. Amitava Choudhury
This paper describes an efficient technique of locating and
extracting license plate and recognizing each segmented
character. The proposed model can be subdivided into four
parts- Digitization of image, Edge Detection, Separation of
characters and Template Matching. In this work, we propose a
method which is based on morphological operations where
different Structuring Elements (SE) are used to maximally
eliminate non-plate region and enhance plate region.
Character segmentation is done using Connected Component
Analysis. Correlation based template matching technique is
used for recognition of characters. This system is
implemented using MATLAB7.4.0. The proposed system is
mainly applicable to Indian License Plates.
A Novel Framework For Numerical Character Recognition With Zoning Distance Fe...IJERD Editor
Advancements of Computer technology has made every organization to implement the automatic processing systems for its activities. One of the examples is the recognition of handwritten characters, which has always been a challenging task in image processing and pattern recognition. In this paper we propose Zone based features for recognition of the handwritten characters. In this zoning approach a digit image is divided into 8x8 zones and centre pixel is computed for each zone. This procedure is sequentially repeated for entire zone. Finally features are extracted for classification and recognition.
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.
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.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
AKS UNIVERSITY Satna Final Year Project By OM Hardaha.pdf
Bangla Optical Digits Recognition using Edge Detection Method
1. IOSR Journal of Electronics and Communication Engineering (IOSR-JECE)
e-ISSN: 2278-2834,p- ISSN: 2278-8735.Volume 7, Issue 3 (Sep. - Oct. 2013), PP 19-24
www.iosrjournals.org
www.iosrjournals.org 19 | Page
Bangla Optical Digits Recognition using Edge Detection Method
Md. MosarrafHossain
(Electrical and Electronic Engineering, Eastern University, Bangladesh)
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.
I. Introduction
Human beings are gifted with natural intelligence to recognize letters, voice, numbers, objects and any
kind of optically recognizable characters. However, making a machine to solve these types of problems is a very
difficult task. Pattern recognition is one of the important components of artificial intelligence. Interest in pattern
recognition is aligned with the enormous amount of information that we encounter in our daily life.
Consequently, computerization is desperately needed to handle this huge information. One of the difficult
problems in the field of pattern recognition is Digits Recognition. Since the variation of the objects within each
class is high, besides this, objects from different classes may be quite similar. Although there are challenges but
the ideas and methodologies have been using to solve this problem would be very useful in many of the pattern
recognition problems that include large volume of real-world data. In digits recognition task, formerly a digit is
scanned, other preprocessing tasks need to pass before feature extraction and finally classification by a certain
methodology.
Over the past three to four decades, many different methods have been explored and used in this field
[1][2], including statistical, structural and syntactic methods, mathematical transforms, template (or model)
matching, neural network and expert systems. In general, algorithms with good performance have either large
descriptive complexity or computationally heavy to precisely identify individual character based on the
database. However, more worksare still required before approaching to the human performance.
In this paper, I am going to discuss a first Bangla (Local language)DigitsRecognition system using
detection of four (Top, bottom, right and left) edges touch points and its ratio. This systemworks Off-line.
Detection of Edge Touch Points (ETP) algorithm is working on the specified information or parameters using
logic instead of central database which makes the method faster than the conventional OCR system and
economical. Therefore this paper has been evaluated the performance of Edge Touch Point (ETP) algorithm as
well as ratio of Edge Touch Points to recognizing Bangla Digits correctly by the machine and its applications.
II. Different Area Of Optical Digits Recognition
Optical Digit Recognition deals with the problem of recognizing optically processed digits. Proposed
Bangla ODR is performed off-line after the printing has been completed, as opposed to on-line recognition
where the computer recognizes the characters or digits as they are drawn. Both printed and handwritten
characters may be recognized, but the performance is directly dependents upon the quality of the inputs.In the
figure-1, briefly illustrates the different area of the OCR/ODR system.
Fig. - 1: Different area of Optical Character/Digit Recognition
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III. Components Of An OCR/ODR System
A typical OCR/ODR system consists of several components. In figure- 2, a common setup [2] is
illustrated. The first step in the process is to digitize the analog document using an optical scanner. When the
regions containing texts are located, each symbol is extracted through a segmentation process. The extracted
symbols may then be preprocessed, eliminating noise to facilitate the extraction of features in the next step and
finally recognize the characters/digits through some post processing.
Fig.- 2: Components of typical OCR/ODR system
IV. Bangla Digits
In the following table, given a complete list of Bangla digits corresponding to English digits those need
to recognize by machine using the proposed method. Observing the following table, anyone can experienced
that the shape of the Bangla digit of “০” (zero), “২” (two) and “৪” (four) are almost similar with English digits
“0” (zero), “2” (two) and “8” (eight) respectively.
TABLE- 1: Bangla digits corresponding to English digits
V. Successful Works On OCR For Bangla Characters With Different Methods
TABLE- 2: Most successful works done on OCR for Bangla characters.
Name Proposed Method Accuracy
MuttakinurRahmanChowdhury (Shouro) [3]
[4] [12]
OCRopus 98%
Adnan Md.Shoeb [7] Kohonen Network 98%
Bhattacharya &Choudhuri [11] Multi-resolution wavelet analysis and majority voting
approach
97.16%
ASM MahabubMorshed et.al.[10] Neural network for postal code recognition 92.2%
Dr. M AbulKashem [9] Multilayer feed forward neural network 97%
ArijitSarkar [8] Particle Swarm Optimization 95.10%
VI. Proposed Method
The proposed system works on the basis of Edge Touch Points (ETP) detection method and the ratio of
the touch point which use to determine each Bangla digit uniquely for different fonts.The method of the Digit
image recognition undergoes collecting and sorting out different fonts, re-shaping image, convertingRGB image
into gray-scale, image processing, feature extraction, and classification. After feature extraction, each digit
image is represented as a feature matrix, which is fed to a classifier for obtaining the class identity. The feature
vectors of sample are used to learn the parameters of the classifier. Since Bangla digit provides gray-scale
image, so proposed a process for recognition on gray-scale images directly to improve the recognition
performance. The steps of the projected method are: 1) Flow chart.2) Image processing and 3) uniquely digit
classification. All the mentioned steps implemented using the computer programming languageof MATLAB.
Location
Segmentation
Feature Extraction
Optical
Scanning
Preprocessing
Recognition
Post-processing
Output
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6.1 Flowchart
Fig.-3: Flow chart
6.2 Image processing
First of all, the raw input data that is printed bangle digit’s image from optical scanningselected from
widely used fonts which re-shaped and save in the same directory so that it can read easily in the MATLAB
platform as of the following figure.
Fig.- 4: Scanned or printed Bangla digit images as input.
Then declare or save the image data against a variable (i.e. y) in MATLAB platform that can recall later like the
following figure.
Fig. - 5: (Sutonny72emj6) Fig. - 6: (Padma96emj5)
The return value of “y” is an array containing the image data. If the file contains a gray-scale image, y
is an M-by-N array. If the file contains a true color (RGB) image, y is an M-by-N-by-3 array. For TIFF files
containing color images that use the CMYK color space, in this case,y is an M-by-N-by-4 array. For the file
format [5], following are the companionable formats with our proposed method, listed in alphabetical order.
BMP- Windows Bitmap, CUR- Cursor File, GIF- Graphics Interchange Format, HDF4- Hierarchical Data
Format, ICO- Icon File, JPEG- Joint Photographic Experts Group, JPEG 2000- Joint Photographic Experts
Group 2000, PBM- Portable Bitmap, PCX- Windows Paintbrush, PGM- Portable Gray map, PNG- Portable
Network Graphics, PPM- Portable Pixmap and RAS- Sun Raster.
In the proposed method, used PNG – Portable Network Graphics file format. Initially, whenever a true
color digit images read or declare against any variable which is an M by N by 3 arrays. Each array pointer has a
value as 255 for no data (total white), 0 for full of data (total black) and for mix of black and white data, the
value of pointer will be any value between 255 and 0 (zero), which solely depend on the digit’s image. For the
sakeof analysis, converted true color image into gray-scale which expressed by an M by N arrays and this
process substantially reduces unwanted data and noise.
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Fig.- 7: An M by N array for the image of Bangla digit one (১)
At this stage, performed elementary operation along rows and columns to omit 255 valuesand get
required field of the dark area of the image. With the help of MATLAB, further re-shaped the image of Bangla
digit as rectangular shape containing only the property of the image as follow
Fig. - 8:Initial image Fig.- 9: After row operation Fig. 10: After column operation
Fig.- 11:An M by N array for the image of Bangla digit one (১) after row and column operation.
6.3 Uniquely digit classification
Now it can easily determine the digit by Edge detection technique which constitutes using four touch
points from the M by N image array. Touch points are top touch point, left touch point, right touch point and
bottom touch point shown in the figure-12.
Fig.- 12: Location of touch points
After figured out the touch points of each edge of the image corresponding to the top, left, right and
bottom sides of the image, calculated the position of the touch points along with the edges.
At this stage, found similar touch points for more than one digit when dealing with different fonts and
this is a big challenge to identify each Bangla digit uniquely. To mitigate this problem, introduce a technique
called ratio of touch points. For top touch point ratio, divide the number of top touch points by number of
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columns of the image matrix and similarly for the bottom touch point ratio but for left and right touch point
ratio, divided by number of rows instead of columns of the image.
At this point, determined the range of the edge touch points and correspondingtouch point’s ratio for
each digit from the samples of 56 (7 fonts of each digit * 8 image sizes for each font) and run these parameters
through“AND” and “OR” logical algorithm in the proposed method and successfully recognized Bangla digits
according to the input raw images.
VII. Results
In the proposed method, total 560 raw sample images of the 10 Bangla digits used (7 fonts for each
digit * 8 different size of images for each font * 10 digits) as input and it can recognized 534 digits correctly.
The accuracy for the proposed method is about 95%. This method provides different accuracy for different fonts
but only one font named “Parash”, where it works with 100% accuracy because parameters for the Parash font
falls middle of the range and did not fluctuate for different fonts and image size. A comparison of the accuracy
for the different sample fonts present in the table- 3. On the other hand, for the some Bangla fonts where
accuracy below 95% and the primary reasons are either the parameters aretoocloseor overlapped each other
when increase the number of samples such as Dhakarchithi (93.75%), Karnaphuli (93.75%) and Sutonny
(92.50%). It is clear from the result of the below accuracy table for the different fonts that the percentage of
accuracy closely related with variation of the shape of the Bangla digit images.
TABLE-3: Accuracy on different fonts of the Bangla digits.
VIII. Applications
During the last couple of decades, it has been seen that the widespread presence of commercial Optical
Digit Recognition products meeting the requirement of different fields where mainly use English digits and now
the proposed Bangla ODR method will open doors for our local language of Bangla digits. In
Bangladesh,government owned banks have been using Bangla digits with unique font as of their Bank check
number and maintain documents using Bangla digits. Those criteria makesthe proposed Bangla ODR technique
suitable to atomization the banking operation of our government owned banks, reduce error, improve security
features, increase customer satisfaction by providing efficient and faster services and reduce overall cost. Other
prospective areas are automatic post code reading for mail sorting, Automatic vehicle number-plate reader,
Automatic Text and data entry, Automatic Cartography and form readers and Automatic Vote counting machine
where Bangla digits with specific fonts are used. Also this method can be applied for other languages as well.
IX. Conclusion
Although, the proposed Bangla ODR method is not 100 percent successful for wide range of fonts but
it works very fast compare to other existing ODR with 100% accuracy for specific fonts such as Parash. Another
feature is that the operation of the proposed Bangla ODR technique does not depend on database rather it
dependents on the parameters of edge touch points and its ratio. As a result, this method is first, user friendly
and economical to implement. In the future, the area of recognition of constrained print is expected to decrease.
Importance will then be on the recognition of unconstrained writing, like omnifont[9] and handwriting. This is a
challenge which requires improved recognition techniques. The potential of the future ODR algorithms seems to
lie in the combination of different methods and the use of techniques that are able to utilize largercontext than
current methodologies.
Acknowledgements
I would like to extend my sincere thanks to Mr. Abu Shafin Mohammad MahdeeJameel, Lecturer,
department of EEE , Eastern University to give me the opportunity to work with an innovative topic as well as
his valuable support to fulfill this research paper and honor his immense contributions throughout the process of
study, constant encouragement and his direct guidance. His contribution in the preparation of the concept paper,
literature, and writing this paper is highly acknowledged.
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