Mohammed Khalil - Profile on Academia.edu (original) (raw)

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Papers by Mohammed Khalil

Sensors (Basel, Switzerland), Jan 31, 2016

The deployment of intelligent remote surveillance systems depends on wireless sensor networks (WS... more The deployment of intelligent remote surveillance systems depends on wireless sensor networks (WSNs) composed of various miniature resource-constrained wireless sensor nodes. The development of routing protocols for WSNs is a major challenge because of their severe resource constraints, ad hoc topology and dynamic nature. Among those proposed routing protocols, the biology-inspired self-organized secure autonomous routing protocol (BIOSARP) involves an artificial immune system (AIS) that requires a certain amount of time to build up knowledge of neighboring nodes. The AIS algorithm uses this knowledge to distinguish between self and non-self neighboring nodes. The knowledge-building phase is a critical period in the WSN lifespan and requires active security measures. This paper proposes an enhanced BIOSARP (E-BIOSARP) that incorporates a random key encryption mechanism in a cost-effective manner to provide active security measures in WSNs. A detailed description of E-BIOSARP is pres...

BioMedical Engineering OnLine, 2015

Background: Fingerprint recognition systems essentially require core-point detection prior to fin... more Background: Fingerprint recognition systems essentially require core-point detection prior to fingerprint matching. The core-point is used as a reference point to align the fingerprint with a template database. When processing a larger fingerprint database, it is necessary to consider the core-point during feature extraction. Numerous core-point detection methods are available and have been reported in the literature. However, these methods are generally applied to scanner-based images. Hence, this paper attempts to explore the feasibility of applying a core-point detection method to a fingerprint image obtained using a camera phone. Method: The proposed method utilizes a discrete wavelet transform to extract the ridge information from a color image. The performance of proposed method is evaluated in terms of accuracy and consistency. These two indicators are calculated automatically by comparing the method's output with the defined core points. Results: The proposed method is tested on two data sets, controlled and uncontrolled environment, collected from 13 different subjects. In the controlled environment, the proposed method achieved a detection rate 82.98%. In uncontrolled environment, the proposed method yield a detection rate of 78.21%. Conclusion: The proposed method yields promising results in a collected-image database. Moreover, the proposed method outperformed compare to existing method.

The Scientific World Journal, 2014

This paper presents a novel watermarking method to facilitate the authentication and detection of... more This paper presents a novel watermarking method to facilitate the authentication and detection of the image forgery on the Quran images. Two layers of embedding scheme on wavelet and spatial domain are introduced to enhance the sensitivity of fragile watermarking and defend the attacks. Discrete wavelet transforms are applied to decompose the host image into wavelet prior to embedding the watermark in the wavelet domain. The watermarked wavelet coefficient is inverted back to spatial domain then the least significant bits is utilized to hide another watermark. A chaotic map is utilized to blur the watermark to make it secure against the local attack. The proposed method allows high watermark payloads, while preserving good image quality. Experiment results confirm that the proposed methods are fragile and have superior tampering detection even though the tampered area is very small.

BioMedical Engineering OnLine, 2016

Due to the increase in security requirements, biometric systems have been commonly utilized in ma... more Due to the increase in security requirements, biometric systems have been commonly utilized in many recognition applications, and it becomes one of the most intensive fields of biometrics research areas. In this paper, we present a fingerprint classification into sub fingerprint dataset in order to optimize the searching and minimized the computational cost for large dataset. We used PCA, LDA, L-LDA and BPN for classification of fingerprint into sub dataset.

… Journal of Physical …, Jan 1, 2010

… (FutureTech), Jan 1, 2010

The International Arab …, Jan 1, 2008

Digital Signal Processing, Jan 1, 2010

Proceedings of The 4th …, Jan 1, 2008

In this study, we statistically analyzed biometric-fingerprint images for personal identification... more In this study, we statistically analyzed biometric-fingerprint images for personal identification. For each of the original images, a 129 × 129 region of interest was extracted and transformed into a co-occurrence matrix. Four different types of relative position distances were used to generate these matrices. The results were then analyzed twice: first by the Program for Rate Estimation and Statistical Summaries (PRESS) and then by the Pattern Recognition and Image Processing Laboratory (FVC2002) testing protocol. The efficiency of the proposed method was demonstrated by the experimental results. In addition, it was found that greater relative-position distances produced lower error equal rates.

Anti-Counterfeiting, Security and …

In this paper, an enhanced image-based fingerprint verification algorithm is presented that impro... more In this paper, an enhanced image-based fingerprint verification algorithm is presented that improves matching accuracy by overcoming the shortcomings of previous methods due to poor image quality. It reduces multi-spectral noise by enhancing a fingerprint image to accurately and reliably determine a reference point and then extracts a 129 X 129 block, making the reference point its center. From the 12 co-occurrence matrices, four statistical descriptors are computed. Experimental results show that the proposed method has more accurate and performance than other methods the average false acceptance rate (FAR) is 0.48% and the average false rejection rate (FRR) is 0.18%.

Signal Processing and …

In this paper, a new fingerprint verification algorithm is presented that improves matching accur... more In this paper, a new fingerprint verification algorithm is presented that improves matching accuracy by overcoming the shortcomings of previous methods due to poor image quality. It reduces multi-spectral noise by enhancing a fingerprint image to accurately and reliably determine a reference point using the orientation reliability and then extract a 129 X 129 block, making the reference point its center. From the 16 co-occurrence matrices, four statistical descriptors are computed. The experimental results have been analyzed using FVC testing protocol; the equal error rate (EER) is 0.32%. Furthermore, the comparison with other methods shows that the proposed method is more accurate and robust for reliable fingerprint verification.

2009 Second International …, Jan 1, 2009

In this paper, a fingerprint verification method is presented that improves matching accuracy by ... more In this paper, a fingerprint verification method is presented that improves matching accuracy by overcoming the shortcomings of previous methods due to missing some minutiae, non-linear distortions, and rotation and distortion variations. It reduces multi-spectral noise by enhancing a fingerprint image to accurately and reliably determine a reference point and then extract a 129 X 129 block, making the reference point its center. From the 4 co-occurrence matrices four statistical descriptors are computed. Experimental results show that the proposed method is more accurate than other methods the average false acceptance rate (FAR) is 0.62%, the average false rejection rate (FRR) is 0.08%, and the equal error rate (EER) is 0.35%.