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In order to classify the eaglewood, the work proposed a method of wood fiber segmentation and characteristic extraction based on the eaglewood micrographs. The active contour model was used to extract the contours of the eaglewood micrographs. After screening of wood fiber, the geometric features and shape factors were extracted to form characteristic vectors. After that, SVM was used to achieve the...
Text recognition has revolutionized the world of image processing and intelligent transportation system (ITS). It opened several possibilities to traditional ITS concept. Advancement in text recognition has made it possible to implement text recognition in ITS. Traffic panel text recognition, a real time application is considered as a key addition to the revolution in modern ITS. This research aims...
Arabic script is cursive in both printed and handwritten forms. This intrinsic nature of cursiveness renders the segmentation task challenging. An Arabic word generally consists of multiple parts known as Parts of Arabic Words (PAWs) or simply sub-words. Sub-words share the same vertical space quite frequently which makes vertical projection segmentation technique inefficient. Several Arabic letters...
Buttons is closely related to human life. The management of buttons in a button factory is very complex because there is a huge number of button types. In order to simplify the management complexity, this paper has proposed a method of multi-template matching to identify the buttons and automatically encode the buttons according to rules in the International Commodity Code so that button libarey can...
Tamil is one of the oldest languages in the world, spoken in Tamil Nadu, South India, which is inherited from Brahmi Script. The main source of information about history are the stone inscriptions. OCR aids in digitizing Tamil scripts from the ancient and old era to the latest, making its access easy through Internet. Ancient Tamil character recognition from stone inscription is a challenge due to...
Resolving ambiguity within mathematical symbols is essential for recognition of mathematical expressions. In this paper, we focus on the resolving ambiguities in mathematical symbols and propose a novel recognition technique that has been tested over large number of ambiguous mathematical symbols obtained from different categories including factoring formula, algebra identity, geometric progression,...
Handwritten character recognition has been emerging topic studied in the last half century and shape up to the level which is sufficient to develop a technology driven application. Now the rapidly increase in the computation power, CR creates an increasing demand for new emerging applications, which require more advanced methodologies. The problem of character segmentation and its recognition in India...
Urdu Nastaleeq is a highly cursive, context sensitive language, written diagonally from top right to bottom left. This makes it difficult to segment the partial word or a complete word into characters. Further due to stacking of characters, the segmentation at the character level is hard to perform. Some researchers have performed the segmentation and have succeeded to a good extent, but still some...
The present work demonstrates a novel scheme for recognising Bengali handwritten consonants by exploring the primitive set of strokes that construct the characters. The Bengali consonants are first manually analysed in order to decompose them into their constituent pattern primitives. Once an exhaustive list of such primitives are prepared, a scheme based on mathematical morphology is devised to identify...
Optical Character Recognition (OCR) is one of key research areas of Artificial Intelligence (AI), and image text recognition is one of challenging fields of OCR. Presented work offers a character recognition system for cursive script (e.g., Arabic, Urdu, etc.) segmented characters from their images. Presented methodology consists of phases namely (1) Image Acquisition, (2) Preprocessing, (3) Chain...
Sindhi language is script language like Arabic and Persian. It's origin is 2500 years old and spoken in various countries in Asia. In this paper, we propose an Optical Character Recognition (OCR) system which recognizes handwritten Sindhi numeral expressions (i.e. Sindhi handwritten numeral strings) without using common input devices such as keyboard and storage device memory. Our experiments focus...
Urdu Nastaleeq is a highly cursive, context sensitive language, written diagonally from top right to bottom left that makes it difficult to segment the partial word or a compete word into characters. Further due to stacking of characters, the segmentation at the character level is hard to perform. Some researchers have performed the ligature level segmentation and have succeeded to a great extent,...
Immense analysis has been done on optical character recognition (OCR). Numerous works has stated for English, Chinese, Devanagari, Malayalam, Arabic scripts, etc. Segmentation has imp phase in OCR and various articles have been published on different segmentation methods like Thinning, histogram etc for different script during last few years. Generally there is not work done on Overlapped and touching...
License plate image binarization is a critical step in Automatic Number Plate Recognition(ANPR) systems and is essential for character segmentation. Generally Otsu(global) or adaptive(local) thresholding methods are commonly used, but each of them may have a shortcoming in terms of segmenting all the characters accurately or Optical Character Recognition(OCR) reading when the plate is not cropped...
Today, Arabic is one of the big challenges in Optical Character Recognition (OCR) to support a digital communication. There are many research on arabic OCR, either printed or handwritten input. However, the research on arabic OCR with harakat is still little due to the high degree of difficulty in segmentation techniques. In this paper, we propose a new segmentation scheme of the arabic character...
We introduce a method for content-based document image retrieval (CBDIR) of handwritten queries that is both segmentation and recognition-free. We first demonstrate that our method is underpinned by a theoretical model that exploits the Bayes' rule. Next, we present an algorithmic implementation that takes into account real world retrieval challenges caused by handwriting fluctuations and style variations...
In this work, an approach for Arabic handwriting word segmentation is proposed. In this approach words are over-segmented and the segmentation points (SPs) are then validated. As the validation stage accuracy controls the whole system accuracy, an improved validation approach is proposed to alleviate other approaches' limitations and enhances the accuracy. In this validation approach, a set of zoning...
Development of Optical Character Recognition (OCR) for printed Roman script is still an active area of research. Automatic Style Identification (ASI) can be used to improve the performance of OCR system and keyword spotting techniques for printed Roman script. This paper proposes a two stage font invariant technique for detection of italic, bold, underlined, normal and all capital styled words for...
There is an urgent need for reliable and efficient systems for off-line automatic reading of machine printed Arabic texts. A partial list of applications that may use such system includes searching and reading in scanned books and manuscript as a part of digital libraries; recognizing text on digitized maps, vehicle license plates, road signs and others. In this research we aim to contribute to the...
Road sign recognition is considered to be one of the most fascinating and interesting field of research in intelligent vehicle and machine learning. Road signs are typically placed either by the roadside or above roads. They provide important information in order to make driving safer and easier. This paper proposes an algorithm that recognizes Bangla road sign with a better percentage. The algorithm...
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