Preferred Language
Articles
/
dhYLAIoBVTCNdQwCO49X
Stamps extraction using local adaptive k- means and ISODATA algorithms
...Show More Authors

<span>One of the main difficulties facing the certified documents documentary archiving system is checking the stamps system, but, that stamps may be contains complex background and surrounded by unwanted data. Therefore, the main objective of this paper is to isolate background and to remove noise that may be surrounded stamp. Our proposed method comprises of four phases, firstly, we apply k-means algorithm for clustering stamp image into a number of clusters and merged them using ISODATA algorithm. Secondly, we compute mean and standard deviation for each remaining cluster to isolate background cluster from stamp cluster. Thirdly, a region growing algorithm is applied to segment the image and then choosing the connected region to produce a binary mask for the stamp area. Finally, the binary mask is combined with the original image to extract the stamp regions. The results indicate that the number of clusters can be determined dynamically and the largest cluster that has minimum standard deviation (i.e., always the largest cluster is the background cluster). Also, show that the binary mask can be established from more than one segment to cover are all stamp’s disconnected pieces and it can be useful to remove the noise appear with stamp region.</span>

Scopus Crossref
View Publication
Publication Date
Wed Aug 27 2025
Journal Name
Baghdad Science Journal
A Clustering Technique Based on the Hard K-Means (H.KM.) Method to Determine the Governorate That Have More Influence for Spreading COVID-19 in the Kingdom of Saudi Arabia
...Show More Authors

View Publication
Scopus Clarivate Crossref
Publication Date
Sat Oct 04 2025
Journal Name
Mesopotamian Journal Of Computer Science
Enhanced IOT Cyber-Attack Detection Using Grey Wolf Optimized Feature Selection and Adaptive SMOTE
...Show More Authors

The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat

... Show More
View Publication Preview PDF
Scopus (1)
Scopus Crossref
Publication Date
Sat Jun 01 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Lung cancer classification using data mining and supervised learning algorithms on multi-dimensional data set
...Show More Authors

These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t

... Show More
View Publication Preview PDF
Scopus (49)
Scopus
Publication Date
Sun May 01 2016
Journal Name
Iosr Journal Of Computer Engineering
Combining Arabic Nested Noun Compound and Collocation Extraction Using Linguistic and Statistical Approach
...Show More Authors

View Publication
Crossref (1)
Crossref
Publication Date
Wed Nov 06 2024
Journal Name
2024 17th International Conference On Development In Esystem Engineering (dese)
Reducing Bandwidth and Storage Requirements for Surveillance Videos Using ROI Extraction and Compression
...Show More Authors

View Publication
Crossref (1)
Scopus Crossref
Publication Date
Thu Apr 01 2021
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Automatic human ear detection approach using modified adaptive search window technique
...Show More Authors

View Publication
Scopus (4)
Crossref (2)
Scopus Crossref
Publication Date
Wed Apr 01 2015
Journal Name
2015 Annual Ieee Systems Conference (syscon) Proceedings
Automatic generation of fuzzy classification rules using granulation-based adaptive clustering
...Show More Authors

View Publication
Scopus (4)
Crossref (4)
Scopus Crossref
Publication Date
Sun May 01 2016
Journal Name
International Journal Of Computer Applications
Lossless Image Compression using Adaptive Predictive Coding of Selected Seed Values
...Show More Authors

Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Distribution system performance improvement by optimal renewable energy placement using swarm algorithms
...Show More Authors

View Publication
Scopus Crossref
Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
...Show More Authors

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

... Show More