Prof. Dr. Muhammad Ali Qureshi | The Islamia University of Bahawalpur (original) (raw)

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Papers by Prof. Dr. Muhammad Ali Qureshi

The CEED2016 is newly developed image database dedicated for contrast enhancement evaluation. The... more The CEED2016 is newly developed image database dedicated for contrast enhancement evaluation. The database contains 30 original color images and 180 enhanced images obtained using six different CE methods. The database is built with our own captured images and some common pictures used by the image processing community. The subjective experiments were performed at Universite Paris 13 at Laboratoire de Traitement et Transport de l'Information (L2TI). The images were displayed on a calibrated LCD monitor in a dark room environment to avoid any problem with the illumination adaptation of background. Twenty-three observers, 10 experts, and 13 non-experts, from different age groups, gender, and background participated in the experiments. To obtain the ranking scores, we adopted a balanced pairwise preference based ranking protocol. The interface for the subjective experiments was developed in Matlab, where, for each original image, we randomly displayed all possible pair combinations of enhanced images to the observers. We also showed the original image in the center of the screen (a pair of enhanced images are to its left and right), to facilitate the analysis of after effects of CE. The observers had the choice to rank equally similar stimuli. In the PC ranking protocol, each enhanced image is compared with the others in pairs and ranking results are stored in a preference matrix.

Applied Sciences

The requirement of mounting several access points and base stations is increasing tremendously du... more The requirement of mounting several access points and base stations is increasing tremendously due to recent advancements and the need for high-data-rate communication services of 5G and 6G wireless communication systems. In the near future, the enormous number of these access points might cause a mess. In such cases, an optically transparent antenna (OTA) is the best option for making the environment more appealing and pleasant. OTAs provide the possible solution as these maintain the device aesthetics to achieve transparency as well as fulfill the basic coverage and bandwidth requirements. Various attempts have been made to design OTAs to provide coverage for wireless communication, particularly for the dead zones. These antennas can be installed on building windows, car windscreens, towers, trees, and smart windows, which enables network access for vehicles and people passing by those locations. Several transparent materials and techniques are used for transparent antenna design....

2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP)

An effective contrast enhancement method should not only improve the perceptual quality of an ima... more An effective contrast enhancement method should not only improve the perceptual quality of an image but should also avoid adding any artifacts or affecting naturalness of images. This makes Contrast Enhancement Evaluation (CEE) a challenging task in the sense that both the improvement in image quality and unwanted side-effects need to be checked for. Currently, there is no single CEE metric that works well for all kinds of enhancement criteria. In this paper, we propose a new Multi-Criteria CEE (MCCEE) measure which combines different metrics effectively to give a single quality score. In order to fully exploit the potential of these metrics, we have further proposed to apply them on the decomposed image using wavelet transform. This new metric has been tested on two natural image contrast enhancement databases as well as on medical Computed Tomography (CT) images. The results show a substantial improvement as compared to the existing evaluation metrics. The code for the metric is available at: https://github.com/zakopz/MCCEE-Contrast-Enhancement-Metric

Optical Engineering, 2020

TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, 2019

IET Image Processing, 2019

Journal of Visual Communication and Image Representation, 2017

Multimedia Tools and Applications, 2016

This paper presents a robust method for passive content authentication of gray and color images. ... more This paper presents a robust method for passive content authentication of gray and color images. The idea is to capture local and global artifacts resulting from the image manipulation through combining intra-block Markov features in both LBP and DCT domains. An optimized support-vector machine with radial-basis kernel is then trained to classify images as being tampered or authentic. We intensively investigate the authentication capabilities of the proposed method for separate color channels and for various combinations of them. The proposed method, without and withfeature-level fusion, is evaluated on three benchmark datasets with a variety of forgery and post-processing operations. The results show that fusing Markov features from LBP and DCT modalities leads to consistent improvement in terms of detection accuracy as compared to the state-of-the-art passive methods. Furthermore, using information from all YCbCr channels help enhancing the detection rate to more than 99.7 % on CASIA TIDE v2.0 image collection.

International Journal of Computer and Electrical Engineering, 2012

2018 Colour and Visual Computing Symposium (CVCS), 2018

For the first time, a database dedicated to contrast enhancement performance evaluation is propos... more For the first time, a database dedicated to contrast enhancement performance evaluation is proposed. This database has recently been developed by our group. In this paper, a detailed description of this database and the methodology we used to build it are discussed. We show that the perceptual quality of contrasted images is related to some specific distortions and artifacts that should be taken into account when building such a database. To this end, we provide some guidelines on how to build a database suitable for testing contrast enhancement quality evaluation metrics, and how to use a psychophysical experiment to obtain the quality judgments for this database. Some open problems and new ideas for using and extending this database are also discussed. The Contrast Enhancement Evaluation Database (CEED), is made publicly accessible through http://dx.doi.org/10.17632/3hfzp6vwkm.3.

2022 IEEE International Conference on Image Processing (ICIP)

SEG Technical Program Expanded Abstracts 2015, 2015

Due to recent substantial development in the field of wireless communication, there is a need to ... more Due to recent substantial development in the field of wireless communication, there is a need to maximize spectral efficiency so that the extensive increase in traffic can be accommodated efficiently. Smart antenna system is a major source to maximize spectral efficiency and capacity of the wireless networks. It consists of an adaptive antenna array that continuously adjusts its radiation characteristics (beam-width of main lobe, side lobe levels and position of nulls) to produce narrow beam in the direction of arrival (DOA) of desired signal and to place nulls in the DOA of interferer signals so that maximum SINR (Signal to Interference and Noise Ratio) is obtained. Smart antennas are becoming more popular now a days due to extensive advancement in the field of digital signal processing and real time implementation of adaptive signal processing techniques on FPGA’s. In this paper we analyze various adaptive beamforming algorithms including LMS (Least Mean Squares), CMA (Constant Modulus Algorithm), RLS (Recursive Least Squares) and CGM (Conjugate Gradient Method) through simulating different parameters like radiation pattern, amplitude response, mean square error and absolute weights of an N-element array for a certain number of iterations. The obtained simulation results are very helpful to evaluate performance and quality of adaptive beamforming algorithms. KeywordsLMS; RLS; CGM; CMA; SINR; Adaptive Beamforming; Smart Antenna; Digital Signal Processing.

Energies

Phasor measurement unit (PMU) technology is a need of the power system due to its better resoluti... more Phasor measurement unit (PMU) technology is a need of the power system due to its better resolution than conventional estimation devices used for wide-area monitoring. PMUs can provide synchronized phasor and magnitude of voltage and current measurements for state estimation of the power system to prevent blackouts. The drawbacks of a PMU are the high cost of the device and its installation. The main aspect of using PMUs in electrical networks is the property to observe the adjacent buses, thereby making it possible to observe the system with fewer PMUs than the number of buses through their optimal placement. In the last two decades, exhaustive research has been done on this issue. Considering the importance of this field, a comprehensive review of the progress achieved until now is carried out and the limitations of existing reviews in the literature are highlighted. This paper can be seen as a major attempt to provide an up-to-date review of the research work carried out in this ...

In this paper, we explore how to computationally characterize subsurface geological structures pr... more In this paper, we explore how to computationally characterize subsurface geological structures presented in seismic volumes using texture attributes. For this purpose, we conduct a comparative study of typical texture attributes presented in the image processing literature. We focus on spatial attributes in this study and examine them in a new application for seismic interpretation, i.e., seismic volume labeling. For this application, a data volume is automatically segmented into various structures, each assigned with its corresponding label. If the labels are assigned with reasonable accuracy, such volume labeling will help initiate an interpretation process in a more effective manner. Our investigation proves the feasibility of accomplishing this task using texture attributes. Through the study, we also identify advantages and disadvantages associated with each attribute.

2020 IEEE 23rd International Multitopic Conference (INMIC)

Attendance marking is a common activity to keep track of the presence of students daily in all ac... more Attendance marking is a common activity to keep track of the presence of students daily in all academic institutions at all grades. Traditional approaches for marking attendance were manual. These approaches are accurate without a chance of marking fake attendance but these are time-consuming and laborsome for a large number of students. To overcome the drawbacks of manual systems, automated systems are developed using radio frequency identification-based scanning, fingerprint scanning, Face-recognition, and Iris scanning based biometric systems. Each system has its pros and cons. Besides, all of these systems suffer from the limitation of human intervention to mark the attendance one by one at a time. To overcome the limitations of existing manual and automated attendance systems, in this work, we propose a robust and efficient attendance marking system from a single group image using face detection and recognition algorithms. In this system, a group image is captured from a high-resolution camera mounted at a fixed location to capture the group image for all the students sitting in a classroom. Next, the face images are extracted from the group image using a popular Viola-Jones algorithm followed by recognition using a convolutional neural network trained on the face database of students. We tested our system for different types of group images and types of databases. Our experimental results show that the proposed framework outperforms other attendance marking systems in terms of efficiency and ease of use and implementation. The proposed system is an autonomous attendance system that requires less human-machine interaction, making it possible to easily incorporate in a smart classroom.

Electric Power Systems Research

Abstract Nowadays Non-Intrusive Load Monitoring (NILM) is considered a hot topic among researcher... more Abstract Nowadays Non-Intrusive Load Monitoring (NILM) is considered a hot topic among researchers. The energy disaggregation datasets are used as the benchmark to validate the performance of energy disaggregation algorithms. It is indeed rather difficult to record the load monitoring of devices and appliances; therefore various benchmarking datasets have been proposed during the past few years. This paper presentsa comprehensive review of 42 NILM datasets aided by comparison tables, generated to elaborate on the diverse features of existing datasets. Moreover, the strengths and limitations of present NILM datasets are highlighted with an outlook on present challenges and future research directions as a contribution to the field of energy disaggregation and load identification. The review will help the researchers to evaluate the performance of new NILM algorithms. We believe that this work could be served as a guideline and can potentially open new research perspectives to the scientific community working on developing new NILM datasets.