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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control)
Shaimaa H. Shaker
University of Technology
Computer Science & IT Electrical & Electronics Engineering

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Technique for recognizing faces using a hybrid of moments and a local binary pattern histogram Raheem Ogla; Ali Adel Saeid; Shaimaa H. Shaker
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2571-2581

Abstract

The face recognition process is widely studied, and the researchers made great achievements, but there are still many challenges facing the applications of face detection and recognition systems. This research contributes to overcoming some of those challenges and reducing the gap in the previous systems for identifying and recognizing faces of individuals in images. The research deals with increasing the precision of recognition using a hybrid method of moments and local binary patterns (LBP). The moment technique computed several critical parameters. Those parameters were used as descriptors and classifiers to recognize faces in images. The LBP technique has three phases: representation of a face, feature extraction, and classification. The face in the image was subdivided into variable-size blocks to compute their histograms and discover their features. Fidelity criteria were used to estimate and evaluate the findings. The proposed technique used the standard Olivetti Research Laboratory dataset in the proposed system training and recognition phases. The research experiments showed that adopting a hybrid technique (moments and LBP) recognized the faces in images and provide a suitable representation for identifying those faces. The proposed technique increases accuracy, robustness, and efficiency. The results show enhancement in recognition precision by 3% to reach 98.78%.
Extraction and segmentation process for the Iraqi paper currency Shaimaa Hameed Abd; Bassam H. Abd; Ivan A. Hashim; Shaimaa H. Shaker
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 3: June 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i3.23299

Abstract

Different application like image segmentation, moving objects detection and objects tracking, required an object detection and segmentation techniques. Recently, these techniques become so important especially when only a specific part of image is important. This research paper presents an efficient algorithm that employed for objects detection and extraction process. This algorithm consists of a several steps and the validity of this algorithm is measured based on different denomination of Iraqi currency. These steps arrange as following: image conversion, deleting small and unnecessary objects from images, extraction of interest objects boundary, finally calculating the rotation angle automatically, and rotate image based on the calculated angle. The validity of algorithm measured on the seven denominations of Iraqi currency (250, 500, 1000, 5000, 10000, 25000, and 50000). This image saved in a database that contain 40 images for each denomination and the total images for all denominations are 280 images. After testing the validity of designed algorithm on all captured image, the algorithm shows high accuracy which equally to 99.6%.
Multi-level encryption for 3D mesh model based on 3D Lorenz chaotic map and random number generator Nashwan Alsalam Ali; Abdul Monem S. Rahma; Shaimaa H. Shaker
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp6486-6495

Abstract

The increasing 3D model applications in various areas of life and widespread use like industry leads to 3D models being stolen and attacked by hackers; therefore, 3D model protection is a fundamental matter nowadays. In this paper, the proposed scheme will provide stringent security for the 3D models by implementing multiple levels of security with preserving the original dimensionality of the 3D model using the weight factor (w). The first level of security is achieved by applying a shuffling process for the vertices based on a key from random number generator (RNG), which provides good confusion. The second level is implemented by modifying the vertices values based on 3D keys from 3D Lorenz chaotic map, which provides good diffusion. The proposed scheme was applied on different 3D models varying in the vertices and faces number. The results illustrate that the proposed scheme deforms the entire 3D model based on Hausdorff distance (HD) approximately 100 after the encryption process, making it resist statistical attack. The scheme provides high security against brute force attack because it has a large key space equal to 10,105 and high security against deferential attack through secret key sensitivity using number of pixels change rate (NPCR) near to 99:6% and unified average changing intensity (UACI) near to 33:4%.
Co-Authors Abdul Monem S. Rahma Ali Adel Saeid Bassam H. Abd Ivan A. Hashim Nashwan Alsalam Ali Raheem Ogla Shaimaa Hameed Abd