scholarly journals Automatic Removal of Handwritten Annotations from Between-text-lines and Inside-text-line Regions of a Printed Text Document

2015 ◽  
Vol 45 ◽  
pp. 205-214
Author(s):  
P. Nagabhushan ◽  
Rachida Hannane ◽  
Abdessamad Elboushaki ◽  
Mohammed Javed
Keyword(s):  
Text Line ◽  
Text Document ◽  
Printed Text ◽  
Automatic Removal

Automatic Anonymization of Printed-Text Document Images

2018 ◽  
pp. 145-152
Author(s):  
Ángel Sánchez ◽  
José F. Vélez ◽  
Javier Sánchez ◽  
A. Belén Moreno
Keyword(s):  
Document Images ◽  
Text Document ◽  
Printed Text

scholarly journals Printed Texts Tracking and Following for a Finger-Wearable Electro-Braille System Through Opto-electrotactile Feedback

2021 ◽  
Author(s):  
Mehdi Rahimi ◽  
Yantao Shen ◽  
Zhiming Liu ◽  
Fang Jiang
Keyword(s):  
Real Time ◽  
Optical Character Recognition ◽  
Text Processing ◽  
Tactile Display ◽  
Sensory Substitution ◽  
Processing Unit ◽  
Text Line ◽  
Imaging Device ◽  
Substitution System ◽  
Printed Text

This paper presents our recent development on a portable and refreshable text reading and sensory substitution system for the blind or visually impaired (BVI), called Finger-eye. The system mainly consists of an opto-text processing unit and a compact electro-tactile based display that can deliver text-related electrical signals to the fingertip skin through a wearable and Braille-dot patterned electrode array and thus delivers the electro-stimulation based Braille touch sensations to the fingertip. To achieve the goal of aiding BVI to read any text not written in Braille through this portable system, in this work, a Rapid Optical Character Recognition (R-OCR) method is firstly developed for real-time processing text information based on a Fisheye imaging device mounted at the finger-wearable electro-tactile display. This allows real-time translation of printed text to electro-Braille along with natural movement of user's fingertip as if reading any Braille display or book. More importantly, an electro-tactile neuro-stimulation feedback mechanism is proposed and incorporated with the R-OCR method, which facilitates a new opto-electrotactile feedback based text line tracking control approach that enables text line following by user fingertip during reading. Multiple experiments were designed and conducted to test the ability of blindfolded participants to read through and follow the text line based on the opto-electrotactile-feedback method. The experiments show that as the result of the opto-electrotactile-feedback, the users were able to maintain their fingertip within a 2mm distance of the text while scanning a text line. This research is a significant step to aid the BVI users with a portable means to translate and follow to read any printed text to Braille, whether in the digital realm or physically, on any surface.

scholarly journals Recognition of Off-line Printed Arabic Text Using Hidden Markov Models

2018 ◽  
Vol 31 (2) ◽  
pp. 230
Author(s):  
Atheel Sabih Shaker
Keyword(s):  
Markov Models ◽  
Hidden Markov ◽  
Arabic Language ◽  
Arabic Text ◽  
Text Line ◽  
Line System ◽  
Persian Language ◽  
Long Time ◽  
Printed Text ◽  
Turkish Language

In this paper, we introduce a method to identify the text printed in Arabic, since the recognition of the printed text is very important in the applications of information technology, the Arabic language is among a group of languages with related characters such as the language of Urdu , Kurdish language , Persian language also the old Turkish language " Ottoman ", it is difficult to identify the related letter because it is in several cases, such as the beginning of the word has a shape and center of the word has a shape and the last word also has a form, either texts in languages where the characters are not connected, then the image of the letter one in any location in the word has been Adoption of programs ready for him A long time. In this paper we present an off-line system to recognize printed Arabic text by using Hidden Markov Model with the aid  of algorithm  that segment the text line into sections and then into characters.

SOBINMF for Automatic Removal of Ocular Artifacts from the EEG

2015 ◽  
Vol 135 (8) ◽  
pp. 954-962
Author(s):  
Hirohisa Tsubakida ◽  
Yumie Ono ◽  
Atsushi Ishiyama
Keyword(s):  
Automatic Removal ◽  
Ocular Artifacts

An Improved B-hill Climbing Optimization Technique for Solving the Text Documents Clustering Problem

2020 ◽  
Vol 16 (4) ◽  
pp. 296-306 ◽  
Author(s):  
Laith Mohammad Abualigah ◽  
Essam Said Hanandeh ◽  
Ahamad Tajudin Khader ◽  
Mohammed Abdallh Otair ◽  
Shishir Kumar Shandilya
Keyword(s):  
Optimization Technique ◽  
Document Clustering ◽  
Text Clustering ◽  
Hill Climbing ◽  
Text Documents ◽  
Clustering Problem ◽  
Text Document ◽  
Text Information ◽  
Amount Of Knowledge ◽  
The Hill

Background: Considering the increasing volume of text document information on Internet pages, dealing with such a tremendous amount of knowledge becomes totally complex due to its large size. Text clustering is a common optimization problem used to manage a large amount of text information into a subset of comparable and coherent clusters. Aims: This paper presents a novel local clustering technique, namely, β-hill climbing, to solve the problem of the text document clustering through modeling the β-hill climbing technique for partitioning the similar documents into the same cluster. Methods: The β parameter is the primary innovation in β-hill climbing technique. It has been introduced in order to perform a balance between local and global search. Local search methods are successfully applied to solve the problem of the text document clustering such as; k-medoid and kmean techniques. Results: Experiments were conducted on eight benchmark standard text datasets with different characteristics taken from the Laboratory of Computational Intelligence (LABIC). The results proved that the proposed β-hill climbing achieved better results in comparison with the original hill climbing technique in solving the text clustering problem. Conclusion: The performance of the text clustering is useful by adding the β operator to the hill climbing.

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