Journal of theoretical and applied information technology, 2015
High performance phase frequency detector (PFD) is one of the key modules in high speed delay-loc... more High performance phase frequency detector (PFD) is one of the key modules in high speed delay-locked loop (DLL). The operation of DLL depends on the performance of its detector. The demand for the reduction of power dissipation in CMOS design is a challenge in order to optimize circuit power consumption. A low power dynamic pseudo-PMOS PFD is proposed to make DLL system more reliable. In this work NOR gate of typical TSPC PFD is replaced with a low power dissipation pseudo-PMOS AND gate built of 3 PMOS transistors. Pseudo-PMOS AND integrated into proposed TSPC PFD to run maximum frequency at 1G Hz with 1.8 V input power supply. This proposed PFD has been implemented in Mentor Graphics 0.18 μm CMOS process technology and consumed 163.36 μm 2 active layout area with 206 nW total power dissipation will further trim down the total cost of the DLL.
Bulletin of Electrical Engineering and Informatics, 2021
Iris recognition used the iris features to verify and identify the identity of human. The iris ha... more Iris recognition used the iris features to verify and identify the identity of human. The iris has many advantages such as stability over time, easy to use and high recognition accuracy. However, the poor quality of iris images can degrade the recognition accuracy of iris recognition system. The recognition accuracy of this system is depended on the iris pattern quality captured during the iris acquisition. The iris pattern quality can degrade due to the blurry image. Blurry image happened due to the movement during image acquisition and poor camera resolution. Due to that, a deblurring method based on the Wiener filter was proposed to improve the quality of iris pattern. This work is significant since the proposed method can enhance the quality of iris pattern in the blurry image. Based to the results, the proposed method improved the quality of iris pattern in the blurry image. Moreover, it recorded the fastest execution time to improve the quality of iris pattern compared to the ...
Iris recognition has become one of the most prominent biometrics due to its high recognition accu... more Iris recognition has become one of the most prominent biometrics due to its high recognition accuracy, and it is suitable for the verification and identification systems. Most iris recognition systems can recognize human identity especially when the iris region is free from noise. However, the iris region is typically occluded by noise, eyelid and eyelash. The occluded iris can hide rich iris features, which consists fewer iris features in the iris region, thus reducing the recognition accuracy of the system. The occluded iris is also called a non-ideal iris. In this study, an improvement is made to enhance the performance of an existing sub-iris technique. This can overcome the problem of obtaining iris features from the non-ideal iris. Moreover, the proposed method can also reduce the execution time of the iris recognition system. According to the results, the proposed method managed to localize the sub-iris region, while achieving an equal error rate of 3.75%; area under curve of 0.9832; execution time of 0.719 s; and decidability of 2.9332. These metrics are superior to those of other methods.
Digital mammogram has become the most effective technique for early breast cancer detection modal... more Digital mammogram has become the most effective technique for early breast cancer detection modality. Digital mammogram takes an electronic image of the breast and stores it directly in a computer. The aim of this study is to develop an automated system for assisting the analysis of digital mammograms. Computer image processing techniques will be applied to enhance images and this is followed by segmentation of the region of interest (ROI). Subsequently, the textural features will be extracted from the ROI. The texture features will be used to classify the ROIs as either masses or non-masses. In this study normal breast images and breast image with masses used as the standard input to the proposed system are taken from Mammographic Image Analysis Society (MIAS) digital mammogram database. In MIAS database, masses are grouped into either spiculated, circumscribed or ill-defined. Additional information includes location of masses centres and radius of masses. The extraction of the textural features of ROIs is done by using gray level co-occurrence matrices (GLCM) which is constructed at four different directions for each ROI. The results show that the GLCM at 0º, 45º, 90º and 135º with a block size of 8X8 give significant texture information to identify between masses and non-masses tissues. Analysis of GLCM properties i.e. contrast, energy and homogeneity resulted in receiver operating characteristics (ROC) curve area of 84. 0 = Az for Otsu's method, 0.82 for thresholding method and 7. 0 = Az for K-mean clustering. ROC curve area of 0.8-0.9 is rated as good results. The authors' proposed method contains no complicated algorithm. The detection is based on a decision tree with five criterions to be analysed. This simplicity leads to less computational time. Thus, this approach is suitable for automated real-time breast cancer diagnosis system.
Journal of theoretical and applied information technology, 2015
High performance phase frequency detector (PFD) is one of the key modules in high speed delay-loc... more High performance phase frequency detector (PFD) is one of the key modules in high speed delay-locked loop (DLL). The operation of DLL depends on the performance of its detector. The demand for the reduction of power dissipation in CMOS design is a challenge in order to optimize circuit power consumption. A low power dynamic pseudo-PMOS PFD is proposed to make DLL system more reliable. In this work NOR gate of typical TSPC PFD is replaced with a low power dissipation pseudo-PMOS AND gate built of 3 PMOS transistors. Pseudo-PMOS AND integrated into proposed TSPC PFD to run maximum frequency at 1G Hz with 1.8 V input power supply. This proposed PFD has been implemented in Mentor Graphics 0.18 μm CMOS process technology and consumed 163.36 μm 2 active layout area with 206 nW total power dissipation will further trim down the total cost of the DLL.
Bulletin of Electrical Engineering and Informatics, 2021
Iris recognition used the iris features to verify and identify the identity of human. The iris ha... more Iris recognition used the iris features to verify and identify the identity of human. The iris has many advantages such as stability over time, easy to use and high recognition accuracy. However, the poor quality of iris images can degrade the recognition accuracy of iris recognition system. The recognition accuracy of this system is depended on the iris pattern quality captured during the iris acquisition. The iris pattern quality can degrade due to the blurry image. Blurry image happened due to the movement during image acquisition and poor camera resolution. Due to that, a deblurring method based on the Wiener filter was proposed to improve the quality of iris pattern. This work is significant since the proposed method can enhance the quality of iris pattern in the blurry image. Based to the results, the proposed method improved the quality of iris pattern in the blurry image. Moreover, it recorded the fastest execution time to improve the quality of iris pattern compared to the ...
Iris recognition has become one of the most prominent biometrics due to its high recognition accu... more Iris recognition has become one of the most prominent biometrics due to its high recognition accuracy, and it is suitable for the verification and identification systems. Most iris recognition systems can recognize human identity especially when the iris region is free from noise. However, the iris region is typically occluded by noise, eyelid and eyelash. The occluded iris can hide rich iris features, which consists fewer iris features in the iris region, thus reducing the recognition accuracy of the system. The occluded iris is also called a non-ideal iris. In this study, an improvement is made to enhance the performance of an existing sub-iris technique. This can overcome the problem of obtaining iris features from the non-ideal iris. Moreover, the proposed method can also reduce the execution time of the iris recognition system. According to the results, the proposed method managed to localize the sub-iris region, while achieving an equal error rate of 3.75%; area under curve of 0.9832; execution time of 0.719 s; and decidability of 2.9332. These metrics are superior to those of other methods.
Digital mammogram has become the most effective technique for early breast cancer detection modal... more Digital mammogram has become the most effective technique for early breast cancer detection modality. Digital mammogram takes an electronic image of the breast and stores it directly in a computer. The aim of this study is to develop an automated system for assisting the analysis of digital mammograms. Computer image processing techniques will be applied to enhance images and this is followed by segmentation of the region of interest (ROI). Subsequently, the textural features will be extracted from the ROI. The texture features will be used to classify the ROIs as either masses or non-masses. In this study normal breast images and breast image with masses used as the standard input to the proposed system are taken from Mammographic Image Analysis Society (MIAS) digital mammogram database. In MIAS database, masses are grouped into either spiculated, circumscribed or ill-defined. Additional information includes location of masses centres and radius of masses. The extraction of the textural features of ROIs is done by using gray level co-occurrence matrices (GLCM) which is constructed at four different directions for each ROI. The results show that the GLCM at 0º, 45º, 90º and 135º with a block size of 8X8 give significant texture information to identify between masses and non-masses tissues. Analysis of GLCM properties i.e. contrast, energy and homogeneity resulted in receiver operating characteristics (ROC) curve area of 84. 0 = Az for Otsu's method, 0.82 for thresholding method and 7. 0 = Az for K-mean clustering. ROC curve area of 0.8-0.9 is rated as good results. The authors' proposed method contains no complicated algorithm. The detection is based on a decision tree with five criterions to be analysed. This simplicity leads to less computational time. Thus, this approach is suitable for automated real-time breast cancer diagnosis system.
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Papers by Mimi Zaki