41 research outputs found

    The Anatomy of Bangla OCR System for Printed Texts using Back Propagation Neural Network

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    This paper is based on Bangla (National Language of Bangladesh) Optical Character Recognition process for printed texts and its steps using Back Propagation Neural Network. Bangla character recognition is very important field of research because Bangla is most popular language in the Indian subcontinent. Pre-processing steps that follows are Image Acquisition, binarization, background removal, noise elimination, skew angle detection and correction, noise removal, line, word and character segmentations. In the post processing steps various features are extracted by applying DCT (Discrete Cosine Transform) from segmented characters. The segmented characters are then fed into a three layer feed forward Back Propagation Neural Network for training. Finally this network is used to recognize printed Bangla scripts

    Segmentation of Horizontally Overlapping Lines in Printed Indian Scripts

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    Handwritten Script Recognition using DCT, Gabor Filter and Wavelet Features at Line Level

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    In a country like India where more number of scripts are in use, automatic identification of printed and handwritten script facilitates many important applications including sorting of document images and searching online archives of document images. In this paper, a multiple feature based approach is presented to identify the script type of the collection of handwritten documents. Eight popular Indian scripts are considered here. Features are extracted using Gabor filters, Discrete Cosine Transform, and Wavelets of Daubechies family. Experiments are performed to test the recognition accuracy of the proposed system at line level for bilingual scripts and later extended to trilingual scripts. We have obtained 100% recognition accuracy for bi-scripts at line level. The classification is done using k-nearest neighbour classifier

    Character Recognition

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    Character recognition is one of the pattern recognition technologies that are most widely used in practical applications. This book presents recent advances that are relevant to character recognition, from technical topics such as image processing, feature extraction or classification, to new applications including human-computer interfaces. The goal of this book is to provide a reference source for academic research and for professionals working in the character recognition field

    RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

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    Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization
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