Segmentation of cursive text has been one of the major problems in Arabic writing. The problem is the shape of the letter which is context sensitive, depending on it’s location within a word. Many text recognition sy...Segmentation of cursive text has been one of the major problems in Arabic writing. The problem is the shape of the letter which is context sensitive, depending on it’s location within a word. Many text recognition systems recognize text imagery at the character level and assemble words from the recognized characters. Unfortunately this approach does not work with Arabic text. In this paper we describe a new approach to segment Arabic text imagery at a word level, without analyzing individual characters. This approach avoids the problem of individual characters segmentation, and can overcome local errors in character recognition.展开更多
The Arabic Language has a very rich vocabulary. More than 200 million peoplespeak this language as their native speaking, and over 1 billion people use it in severalreligion-related activities. In this paper a new tec...The Arabic Language has a very rich vocabulary. More than 200 million peoplespeak this language as their native speaking, and over 1 billion people use it in severalreligion-related activities. In this paper a new technique is presented for recognizing printedArabic characters. After a word is segmented, each character/word is entirely transformed into afeature vector. The features of printed Arabic characters include strokes and bays in variousdirections, endpoints, intersection points, loops, dots and zigzags. The word skeleton is decomposedinto a number of links in orthographic order, and then it is transferred into a sequence of symbolsusing vector quantization. Single hidden Markov model has been used for recognizing the printedArabic characters. Experimental results show that the high recognition rate depends on the number ofstates in each sample.展开更多
Pali is considered as the language of the canon continued to be influenced by analysts and grammarians,and by the native languages of the countries like Sri Lanka,in which Therava da Buddhism became established over m...Pali is considered as the language of the canon continued to be influenced by analysts and grammarians,and by the native languages of the countries like Sri Lanka,in which Therava da Buddhism became established over many years.The Pali language has been used to write many stone inscriptions in ancient times.For ordinary travelers the recognition of the content of ancient inscriptions and some other written material are not possible.This study has focused to find a solution with a mobile application to recognize Pali characters in a user-friendly User Interface.The character recognition in real time is the most essential part of the study.Machine learning and neural networks are trending technologies adapted for handwriting recognition in some languages.But for many languages this technology has not been developed yet.Pali is one of such languages that had survived until the eighteenth century.In this study the images of Pali letters are identified through a trained Convolution Neural Network(CNN).Python and Android Studio software were used for training process and identifying letters respectively with the developed mobile application.The limited capacity and the processing power of a mobile phone makes it more challenging to run the application.Tensor Flow Lite is end to end open source platform in machine learning.Therefore,Tensor Flow Lite was used in this study.Since the Android mobile is a common equipment which everybody has in modern societies,using this Off-line Pali character Recognition mobile application the archelogy researchers and travelers can use them conveniently to understand the content written in ancient documents.展开更多
Teaching and learning-related activities have embraced digital technology especially,with the current global pandemic restrictions pervaded during the last two years.On the other hand,most of the academic and professi...Teaching and learning-related activities have embraced digital technology especially,with the current global pandemic restrictions pervaded during the last two years.On the other hand,most of the academic and professional presentations are conducted using online platforms.But the presenter-audience interaction is hindered to a certain extent in an online case in contrary to face-to-face where real-time writing is beneficial when sketching is involved.The use of digital pens and pads is a solution for such instances,though the cost of acquiring such hardware is high.Economical solutions are essential as affordability is concerned.In this study,a real-time user-friendly,innovative drawing system is developed to address the issues related to the problems confronted with online presentations.This paper presents the development of an algorithm using Hand Landmark Detection,which replaces chalks,markers and regular ballpoint pens used in conventional communication and presentation,with online platforms.The proposed application in this study is acquired by Python and OpenCV libraries.The letters or the sketches drawn in the air were taken straight to the computer screen by this algorithm.The proposed algorithm continuously identifies the Hand Landmark using the images fed by the web camera,and text or drawing patterns are displayed on the screen according to the movements made by Hand Landmark on the image space.The developed user interface is also user-friendly.Hence the communication of letters and sketches were enabled.Although the concept has been developed and tested,with further research the versatility and accuracy of communication can be enhanced.展开更多
文摘Segmentation of cursive text has been one of the major problems in Arabic writing. The problem is the shape of the letter which is context sensitive, depending on it’s location within a word. Many text recognition systems recognize text imagery at the character level and assemble words from the recognized characters. Unfortunately this approach does not work with Arabic text. In this paper we describe a new approach to segment Arabic text imagery at a word level, without analyzing individual characters. This approach avoids the problem of individual characters segmentation, and can overcome local errors in character recognition.
文摘The Arabic Language has a very rich vocabulary. More than 200 million peoplespeak this language as their native speaking, and over 1 billion people use it in severalreligion-related activities. In this paper a new technique is presented for recognizing printedArabic characters. After a word is segmented, each character/word is entirely transformed into afeature vector. The features of printed Arabic characters include strokes and bays in variousdirections, endpoints, intersection points, loops, dots and zigzags. The word skeleton is decomposedinto a number of links in orthographic order, and then it is transferred into a sequence of symbolsusing vector quantization. Single hidden Markov model has been used for recognizing the printedArabic characters. Experimental results show that the high recognition rate depends on the number ofstates in each sample.
文摘Pali is considered as the language of the canon continued to be influenced by analysts and grammarians,and by the native languages of the countries like Sri Lanka,in which Therava da Buddhism became established over many years.The Pali language has been used to write many stone inscriptions in ancient times.For ordinary travelers the recognition of the content of ancient inscriptions and some other written material are not possible.This study has focused to find a solution with a mobile application to recognize Pali characters in a user-friendly User Interface.The character recognition in real time is the most essential part of the study.Machine learning and neural networks are trending technologies adapted for handwriting recognition in some languages.But for many languages this technology has not been developed yet.Pali is one of such languages that had survived until the eighteenth century.In this study the images of Pali letters are identified through a trained Convolution Neural Network(CNN).Python and Android Studio software were used for training process and identifying letters respectively with the developed mobile application.The limited capacity and the processing power of a mobile phone makes it more challenging to run the application.Tensor Flow Lite is end to end open source platform in machine learning.Therefore,Tensor Flow Lite was used in this study.Since the Android mobile is a common equipment which everybody has in modern societies,using this Off-line Pali character Recognition mobile application the archelogy researchers and travelers can use them conveniently to understand the content written in ancient documents.
文摘Teaching and learning-related activities have embraced digital technology especially,with the current global pandemic restrictions pervaded during the last two years.On the other hand,most of the academic and professional presentations are conducted using online platforms.But the presenter-audience interaction is hindered to a certain extent in an online case in contrary to face-to-face where real-time writing is beneficial when sketching is involved.The use of digital pens and pads is a solution for such instances,though the cost of acquiring such hardware is high.Economical solutions are essential as affordability is concerned.In this study,a real-time user-friendly,innovative drawing system is developed to address the issues related to the problems confronted with online presentations.This paper presents the development of an algorithm using Hand Landmark Detection,which replaces chalks,markers and regular ballpoint pens used in conventional communication and presentation,with online platforms.The proposed application in this study is acquired by Python and OpenCV libraries.The letters or the sketches drawn in the air were taken straight to the computer screen by this algorithm.The proposed algorithm continuously identifies the Hand Landmark using the images fed by the web camera,and text or drawing patterns are displayed on the screen according to the movements made by Hand Landmark on the image space.The developed user interface is also user-friendly.Hence the communication of letters and sketches were enabled.Although the concept has been developed and tested,with further research the versatility and accuracy of communication can be enhanced.
