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Ibrahim S. I. Abuhaiba

dblp:a/ISIAbuhaiba · also I. S. I. Abuhaiba, Ibrahim Soliman I. Abuhaiba · DBLP profile ↗
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13ranked-venue papers
11as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 12 · 10 first-authorDatabases, data management, data science and information retrieval · 3 · 3 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Image recognition and object detection · 44% Graph learning · 44% Segmentation and scene understanding · 13%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › Image recognition and object detection
character recognition
0.011994
Recognition of Handwritten Cursive Arabic Characters · IEEE Trans. Pattern Anal. Mach. Intell. 1994
Computer vision › Segmentation and scene understanding
skeletonization
0.011994
Recognition of Handwritten Cursive Arabic Characters · IEEE Trans. Pattern Anal. Mach. Intell. 1994

Methods — techniques the papers use, named apart from their topics

tree structure matching · 0.0fuzzy constrained character graph models · 0.0
YearPublicationVenuePosition
2013 Efficient iris segmentation method in unconstrained environments
Shaaban Sahmoud, Ibrahim S. I. Abuhaiba
Pattern Recognit.2
1998 Recognition of Off-Line Cursive Handwriting
Ibrahim S. I. Abuhaiba, Murray J. J. Holt
Comput. Vis. Image Underst.1
1996 Processing of binary images of handwritten text documents
Ibrahim S. I. Abuhaiba, Murray J. J. Holt
Pattern Recognit.1
1995 Line extraction and stroke ordering of text pages
abstract
A method is developed to extract lines from pages of handwritten text by finding the shortest spanning tree of a graph formed from the set of main strokes. Main strokes of extracted lines are arranged in the same order as they were written by following the path in which they are contained. Then, every secondary stroke is assigned to the closest main stroke. At the end, an ordered list of main strokes each with the corresponding number of assigned secondary strokes is obtained. Each combination of main-secondary strokes can be the input to a subsequent recognition stage. The method is more suited to variable handwriting.
Ibrahim S. I. Abuhaiba, Murray J. J. Holt
ICDAR1
1995 Processing of text documents: straight line approximation and lost loop recovery
abstract
This paper deals with two different problems in processing of text documents. Firstly, an integrated algorithm that finds a straight line approximation of a textual stroke is described. It has the advantage of using the distance transform of thinned binary images to identify, spurious bifurcation points which are unavoidable when thinning algorithms are used, remove them, and recover the original ones. Secondly, a method is presented to recover loops that become blobs due to blotting. The method depends on removing the pixels whose distance transform exceeds a calculated threshold.
Ibrahim S. I. Abuhaiba, Murray J. J. Holt
ICDAR1
1995 Fuzzy state machines to recognize totally unconstructed handwritten strokes
Ibrahim S. I. Abuhaiba, Murray J. J. Holt
Image Vis. Comput.1
1994 Processing of Off-Line Handwritten Text: Polygonal Approximation and Enforcement of Temporal Information
Ibrahim S. I. Abuhaiba, Murray J. J. Holt
CVGIP Graph. Model. Image Process.1
1994 Straight line approximation and 1D representation of off-line handwritten text
Ibrahim S. I. Abuhaiba, Murray J. J. Holt
Image Vis. Comput.1
1994 Recognition of Handwritten Cursive Arabic Characters
abstract
An automatic off-line character recognition system for handwritten cursive Arabic characters is presented. A robust noise-independent algorithm is developed that yields skeletons that reflect the structural relationships of the character components. The character skeleton is converted to a tree structure suitable for recognition. A set of fuzzy constrained character graph models (FCCGM's), which tolerate large variability in writing, is designed. These models are graphs, with fuzzily labeled arcs used as prototypes for the characters. A set of rules is applied in sequence to match a character tree to an FCCGM. Arabic handwritings of four writers were used in the learning and testing stages. The system proved to be powerful in tolerance to variable writing, speed, and recognition rate.>
Ibrahim S. I. Abuhaiba, Sabri A. Mahmoud, Roger J. Green
IEEE Trans. Pattern Anal. Mach. Intell.1
1993 Totally unconstrained handwritten numeral recognition via fuzzy graphs
abstract
The performance of a novel recognition system which uses fuzzy constrained character graph models (FCCGMs) is investigated for totally unconstrained and handwritten numeral recognition. The system was tested on 1812 unnormalized samples. The reliability, recognition, substitution error, and rejection rates of the system were 97.1%, 90.7%, 2.9%, and 6.4%, respectively.>
Ibrahim S. I. Abuhaiba, Pervez Ahmed
ICDAR1
1993 Restoration of temporal information in off-line arabic handwriting
Ibrahim S. I. Abuhaiba, Pervez Ahmed
Pattern Recognit.1
1993 A fuzzy graph theoretic approach to recognize the totally unconstrained handwritten numerals
Ibrahim S. I. Abuhaiba, P. Ahmed
Pattern Recognit.1
1991 Skeletonization of Arabic characters using clustering based skeletonization algorithm (CBSA)
Sabri A. Mahmoud, Ibrahim S. I. Abuhaiba, Roger J. Green
Pattern Recognit.2