Sharifah Mumtazah Syed Ahmad

Learn More
This paper introduces a new multi-purpose image watermarking algorithm which based on a hybrid of lifting wavelet transform (LWT) and Arnold transform for copyright protection and image authentication. In the proposed scheme, the original image is first decomposed by LWT into four subbands. Then the robust watermark which is a binary logo image is(More)
This paper presents an analysis performance of different features in distinguishing between genuine and forged signatures for HMM based offline signature verification systems. The four offline features include pixel density, centre of gravity, distance and angle. All features considered are local in nature. The analysis technique used here is based on(More)
One of the main difficulties in designing online signature verification (OSV) system is to find the most distinctive features with high discriminating capabilities for the verification, particularly, with regard to the high variability which is inherent in genuine handwritten signatures, coupled with the possibility of skilled forgeries having close(More)
This paper presents an automatic off-line signature verification system that is built using several statistical techniques. The learning phase involves the use of Hidden Markov Modelling (HMM) technique to build a reference model for each local feature extracted from a set of signature samples of a particular user. The verification phase uses three layers(More)
Face as a biometric attribute has been extensively studied over the past few decades. Even though, satisfactory results are already achieved in controlled environments, the practicality of face recognition in realistic scenarios is still limited by several challenges, such as, expression, pose, occlusion, etc. Recently, the research direction is(More)
This paper reports on the effect that the number of samples used in training a signature verification system has on the system’s accuracy which is describes by the pair combination of the system False Acceptance Rate (FAR) and False Rejection Rate (FRR). This paper also describes such an effect on the system Failure to Capture Rate (FCR), which is(More)
Gender as a soft biometric attribute has been extensively investigated in the domain of computer vision because of its numerous potential application areas. However, studies have shown that gender recognition performance can be hindered by improper alignment of facial images. As a result, previous experiments have adopted face alignment as an important(More)