18 research outputs found
USING AN EIGEN VALUES AND SPATIAL FEATURES FOR BUILDING AN IRAQI LICENSE PLATE DETECTOR AND RECOGNIZER
This paper produced a system for license plate recognition problem for Iraqi cars. The system depending on edges and position to locate license plate and character detection within it, for characters’ recognition an Eigen value for prepared templates was used to identify each character with template matching for recognizing government. Euclidian distance is invested for taking a decision; Experiments show that the recognition success was high and precise
A line-based representation for matching words in historical manuscripts
Cataloged from PDF version of article.In this study, we propose a new method for retrieving and recognizing words in historical documents. We represent word images with a set of line segments. Then we provide a criterion for word matching based on matching the lines. We carry out experiments on a benchmark dataset consisting of manuscripts by George Washington, as well as on Ottoman manuscripts. (C) 2011 Elsevier B.V. All rights reserved
Arabic Text Steganography Using Multiple Diacritics
Steganography techniques are concerned with hiding the existence of data in other cover media. Today, text steganography has become particularly popular. This paper presents a new idea for using Arabic text in steganography. The main idea is to superimpose multiple invisible instances of Arabic diacritic marks over each other. This is possible because of the way in which diacritic marks are displayed on screen and printed to paper. Two approaches and several scenarios are proposed. The main advantage is in terms of the arbitrary capacity. The approach was compared to other similar methods in terms of overhead on capacity. It was shown to exceed any of these easily, provided the correct scenario is chosen
Arabic Text Steganography Using Multiple Diacritics
Steganography techniques are concerned with hiding the existence of data in other cover media. Today, text steganography has become particularly popular. This paper presents a new idea for using Arabic text in steganography. The main idea is to superimpose multiple invisible instances of Arabic diacritic marks over each other. This is possible because of the way in which diacritic marks are displayed on screen and printed to paper. Two approaches and several scenarios are proposed. The main advantage is in terms of the arbitrary capacity. The approach was compared to other similar methods in terms of overhead on capacity. It was shown to exceed any of these easily, provided the correct scenario is chosen
Isolated Persian/Arabic handwriting characters: Derivative projection profile features, implemented on GPUs
For many years, researchers have studied high accuracy methods for recognizing the handwriting and achieved many significant improvements. However, an issue that has rarely been studied is the speed of these methods. Considering the computer hardware limitations, it is necessary for these methods to run in high speed. One of the methods to increase the processing speed is to use the computer parallel processing power. This paper introduces one of the best feature extraction methods for the handwritten recognition, called DPP (Derivative Projection Profile), which is employed for isolated Persian handwritten recognition. In addition to achieving good results, this (computationally) light feature can easily be processed. Moreover, Hamming Neural Network is used to classify this system. To increase the speed, some part of the recognition method is executed on GPU (graphic processing unit) cores implemented by CUDA platform. HADAF database (Biggest isolated Persian character database) is utilized to evaluate the system. The results show 94.5% accuracy. We also achieved about 5.5 times speed-up using GPU
A line-based representation for matching words in historical manuscripts
In this study, we propose a new method for retrieving and recognizing words in historical documents. We represent word images with a set of line segments. Then we provide a criterion for word matching based on matching the lines. We carry out experiments on a benchmark dataset consisting of manuscripts by George Washington, as well as on Ottoman manuscripts. © 2011 Elsevier B.V. All rights reserved
Segmentation based Ottoman text and matching based Kufic image analysis
Ankara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2013.Thesis (Master's) -- Bilkent University, 2013.Includes bibliographical references leaves 80-88.Large archives of historical documents attract many researchers from all around
the world. The increasing demand to access those archives makes automatic retrieval
and recognition of historical documents crucial. Ottoman archives are one
of the largest collections of historical documents. Although Ottoman is not a
currently spoken language, many researchers from all around the world are interested
in accessing the archived material. This thesis proposes two Ottoman
document analysis studies; first one is a crucial pre-processing task for retrieval
and recognition which is segmentation of documents. Second one is a more specific
retrieval and recognition problem which aims matching Islamic patterns is
Kufic images. For the first segmentation task, layout, line and word segmentation
is studied. Layout segmentation is obtained via Log-Gabor filtering. Four
different algorithms are proposed for line segmentation and finally a simple morphological
method is preferred for word segmentation. Datasets are constructed
with documents from both Ottoman and other languages (English, Greek and
Bangla) to test the script-independency of the methods. Experiments show that
our segmentation steps give satisfactory results. The second task aims to detect
Islamic patterns in Kufic images. The sub-patterns are considered as basic units
and matching is used for the analysis. Graphs are preferred to represent subpatterns
where graph and sub-graph isomorphism are used for matching them.
Kufic images are analyzed in three different ways. Given a query pattern, all the
instances of the query can be found through retrieval. Going further, through
known patterns images can be automatically labeled in the entire dataset. Finally,
patterns that repeat inside an image can be automatically discovered. As
there is no existing Kufic dataset, a new one is constructed by collecting images
from the Internet and promising results are obtained on this dataset.Adıgüzel, HandeM.S
A Line-based representation for matching words
Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2009.Thesis (Master's) -- Bilkent University, 2009.Includes bibliographical references leaves 46-49.With the increase of the number of documents available in the digital environment,
efficient access to the documents becomes crucial. Manual indexing of the
documents is costly; however, and can be carried out only in limited amounts.
Therefore, automatic analysis of documents is crucial. Although plenty of effort
has been spent on optical character recognition (OCR), most of the existing OCR
systems fail to address the challenge of recognizing characters in historical documents
on account of the poor quality of old documents, the high level of noise
factors, and the variety of scripts. More importantly, OCR systems are usually
language dependent and not available for all languages. Word spotting techniques
have been recently proposed to access the historical documents with the idea that
humans read whole words at a time. In these studies the words rather than the
characters are considered as the basic units. Due to the poor quality of historical
documents, the representation and matching of words continue to be challenging
problems for word spotting. In this study we address these challenges and propose
a simple but effective method for the representation of word images by a
set of line descriptors. Then, two different matching criteria making use of the
line-based representation are proposed. We apply our methods on the word spotting
and redif extraction tasks. The proposed line-based representation does not
require any specific pre-processing steps, and is applicable to different languages
and scripts. In word spotting task, our results provide higher scores than the
existing word spotting studies in terms of retrieval and recognition performances.
In the redif extraction task, we obtain promising results providing a motivation
for further and advanced studies on Ottoman literary texts.Can, Ethem FatihM.S