7 research outputs found
PUBLIC OCR SIGN AGE RECOGNITION WITH SKEW & SLANT CORRECTION FOR VISUALLY IMP AIRED PEOPLE
This paper presents an OCR hybrid recognition model for the Visually Impaired People
(VIP). The VIP often encounters problems navigating around independently because they are
blind or have poor vision. They are always being discriminated due to their limitation which can
lead to depression to the VIP. Thus, they require an efficient technological assistance to help
them in their daily activity. The objective of this paper is to propose a hybrid model for Optical
Character Recognition (OCR) to detect and correct skewed and slanted character of public
signage. The proposed hybrid model should be able to integrate with speech synthesizer for VIP
signage recognition. The proposed hybrid model will capture an image of a public signage to be
converted into machine readable text in a text file. The text will then be read by a speech
synthesizer and translated to voice as the output. In the paper, hybrid model which consist of
Canny Method, Hough Transformation and Shearing Transformation are used to detect and
correct skewed and slanted images. An experiment was conducted to test the hybrid model
performance on 5 blind folded subjects. The OCR hybrid recognition model has successfully
achieved a Recognition Rate (RR) of 82. 7%. This concept of public signage recognition is being
proven by the proposed hybrid model which integrates OCR and speech synthesizer
Investigation of a Kolmogorov Complexity Based Similarity Metric for Content Based Image Retrieval
This paper introduces an image retrieval approach using normalized information distance based similarity metric to determine the difference between the images. The similarity metric is based on Kolmogorov complexity and measures the amount of shared information between images. Although the Kolmogorov complexity is uncomputable, we are following Vitanyi's approach for approximating itComputer Science Departmen
PUBLIC OCR SIGN AGE RECOGNITION WITH SKEW & SLANT CORRECTION FOR VISUALLY IMP AIRED PEOPLE
This paper presents an OCR hybrid recognition model for the Visually Impaired People
(VIP). The VIP often encounters problems navigating around independently because they are
blind or have poor vision. They are always being discriminated due to their limitation which can
lead to depression to the VIP. Thus, they require an efficient technological assistance to help
them in their daily activity. The objective of this paper is to propose a hybrid model for Optical
Character Recognition (OCR) to detect and correct skewed and slanted character of public
signage. The proposed hybrid model should be able to integrate with speech synthesizer for VIP
signage recognition. The proposed hybrid model will capture an image of a public signage to be
converted into machine readable text in a text file. The text will then be read by a speech
synthesizer and translated to voice as the output. In the paper, hybrid model which consist of
Canny Method, Hough Transformation and Shearing Transformation are used to detect and
correct skewed and slanted images. An experiment was conducted to test the hybrid model
performance on 5 blind folded subjects. The OCR hybrid recognition model has successfully
achieved a Recognition Rate (RR) of 82. 7%. This concept of public signage recognition is being
proven by the proposed hybrid model which integrates OCR and speech synthesizer
PUBLIC OCR SIGN AGE RECOGNITION WITH SKEW & SLANT CORRECTION FOR VISUALLY IMP AIRED PEOPLE
This paper presents an OCR hybrid recognition model for the Visually Impaired People
(VIP). The VIP often encounters problems navigating around independently because they are
blind or have poor vision. They are always being discriminated due to their limitation which can
lead to depression to the VIP. Thus, they require an efficient technological assistance to help
them in their daily activity. The objective of this paper is to propose a hybrid model for Optical
Character Recognition (OCR) to detect and correct skewed and slanted character of public
signage. The proposed hybrid model should be able to integrate with speech synthesizer for VIP
signage recognition. The proposed hybrid model will capture an image of a public signage to be
converted into machine readable text in a text file. The text will then be read by a speech
synthesizer and translated to voice as the output. In the paper, hybrid model which consist of
Canny Method, Hough Transformation and Shearing Transformation are used to detect and
correct skewed and slanted images. An experiment was conducted to test the hybrid model
performance on 5 blind folded subjects. The OCR hybrid recognition model has successfully
achieved a Recognition Rate (RR) of 82. 7%. This concept of public signage recognition is being
proven by the proposed hybrid model which integrates OCR and speech synthesizer
Old document image analysis : a texture approach
In this article, we propose a method of characterization of images of old documents based on a texture approach. This
characterization is carried out with the help of a multi-resolution study of the textures contained in the images of the
document. Thus, by extracting five features linked to the frequencies and to the orientations in the different areas of a
page, it is possible to extract and compare elements of high semantic level without expressing any hypothesis about the
physical or logical structure of the analysed documents. Experimentations demonstrate the performance of our
propositions and the advances that they represent in terms of characterization of content of a deeply heterogeneous
corpus.Dans cet article, nous proposons une méthode de caractérisation d’images d’ouvrages anciens basée sur une
approche texture. Cette caractérisation est réalisée à l’aide d’une étude multirésolution des textures
contenues dans les images de documents. Ainsi, en extrayant cinq indices liés aux fréquences et aux
orientations dans les différentes parties d’une page, il est possible d’extraire et de comparer des éléments de
haut niveau sémantique sans émettre d’hypothèses sur la structure physique ou logique des documents
analysés. Des expérimentations montrent la faisabilité de la réalisation d’outils d’aide à la navigation ou d’aide
à l’indexation. Au travers de ces expérimentations, nous mettrons en avant la pertinence de ces indices et les
avancées qu’ils représentent en terme de caractérisation de contenu d’un corpus fortement hétérogène