Nibaran Das

  1. Text Region Extraction from Business Card Images for Mobile Devices.

    Authors: Nibaran Das, Ram Sarkar, Subhadip Basu, Mahantapas Kundu, Mita Nasipuri, Ayatullah Faruk Mollah
    Subjects: Computer Vision and Pattern Recognition
    Abstract

    Designing a Business Card Reader (BCR) for mobile devices is a challenge to
    the researchers because of huge deformation in acquired images, multiplicity in
    nature of the business cards and most importantly the computational constraints
    of the mobile devices. This paper presents a text extraction method designed in
    our work towards developing a BCR for mobile devices. At first, the background
    of a camera captured image is eliminated at a coarse level. Then, various rule
    based techniques are applied on the Connected Components (CC) to filter out the
    noises and picture regions.

  2. Binarizing Business Card Images for Mobile Devices.

    Authors: Nibaran Das, Ram Sarkar, Subhadip Basu, Mahantapas Kundu, Mita Nasipuri, Ayatullah Faruk Mollah
    Subjects: Computer Vision and Pattern Recognition
    Abstract

    Business card images are of multiple natures as these often contain graphics,
    pictures and texts of various fonts and sizes both in background and
    foreground. So, the conventional binarization techniques designed for document
    images can not be directly applied on mobile devices. In this paper, we have
    presented a fast binarization technique for camera captured business card
    images. A card image is split into small blocks. Some of these blocks are
    classified as part of the background based on intensity variance.

  3. Word level Script Identification from Bangla and Devanagri Handwritten Texts mixed with Roman Script.

    Authors: Nibaran Das, Ram Sarkar, Subhadip Basu, Mahantapas Kundu, Mita Nasipuri, Dipak Kumar Basu
    Subjects: Learning
    Abstract

    India is a multi-lingual country where Roman script is often used alongside
    different Indic scripts in a text document. To develop a script specific
    handwritten Optical Character Recognition (OCR) system, it is therefore
    necessary to identify the scripts of handwritten text correctly.

  4. Handwritten Bangla Basic and Compound character recognition using MLP and SVM classifier.

    Authors: Nibaran Das, Bindaban Das, Ram Sarkar, Subhadip Basu, Mahantapas Kundu, Mita Nasipuri
    Subjects: Computer Vision and Pattern Recognition
    Abstract

    A novel approach for recognition of handwritten compound Bangla characters,
    along with the Basic characters of Bangla alphabet, is presented here. Compared
    to English like Roman script, one of the major stumbling blocks in Optical
    Character Recognition (OCR) of handwritten Bangla script is the large number of
    complex shaped character classes of Bangla alphabet. In addition to 50 basic
    character classes, there are nearly 160 complex shaped compound character
    classes in Bangla alphabet.

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