Atif Shahzad

Real-time automatic license plate recognition for CCTV forensic applications

We propose an efficient real-time automatic license plate recognition (ALPR) framework, particularly designed to work on CCTV video footage obtained from cameras that are not dedicated to the use in ALPR. At present, in license plate detection, tracking and recognition are reasonably well-tackled problems with many successful commercial solutions being available. However, the existing ALPR algorithms are based on the assumption that the input video will be obtained via a dedicated, high-resolution, high-speed camera and is/or supported by a controlled capture environment, with appropriate camera height, focus, exposure/shutter speed and lighting settings. However, typical video forensic applications may require searching for a vehicle having a particular number plate on noisy CCTV video footage obtained via non-dedicated, medium-to-low resolution cameras, working under poor illumination conditions. ALPR in such video content faces severe challenges in license plate localization, tracking and recognition stages. This paper proposes a novel approach for efficient localization of license plates in video sequence and the use of a revised version of an existing technique for tracking and recognition. A special feature of the proposed approach is that it is intelligent enough to automatically adjust for varying camera distances and diverse lighting conditions, a requirement for a video forensic tool that may operate on videos obtained by a diverse set of unspecified, distributed CCTV cameras.

Hybrid Artifact Removal for Confocal Microwave Breast Imaging

Several factors determine the effectiveness of an early-stage artifact removal algorithm for the detection of breast cancer using confocal microwave imaging. These factors include the ability to select the correct time window containing the artifact, the ability to remove the artifact while being robust to normal variances, and ability to effectively preserve the tumor response in the resultant signal. Very few (if any) of the existing artifact removal algorithms incorporate all of these qualities. In this letter, a novel hybrid artifact removal algorithm for microwave breast imaging applications is presented, which combines the best attributes of two existing algorithms to effectively remove the early-stage artifact while preserving the tumor response. This algorithm is compared to existing algorithms using a range of appropriate performance metrics.

A Preprocessing Filter for Multistatic Microwave Breast Imaging for Enhanced Tumour Detection

Ultra Wideband Radar imaging has shown promising results in the detection of small tumours within low to medium density human breasts. A wide range of beamforming algorithms has been presented in several recent studies with good tumour localization capabilities, but most of these sufier a deterioration in performance with an increase in breast tissue density. In this paper, a preprocessing fllter is used to compensate for path-dependent attenuation and phase efiects, in conjunction with a range of existing data-dependent and data-independent confocal microwave imaging algorithms. Results indicate that this data preprocessing improves the performance of all beamformers, enabling detection and accurate localization of multiple tumours in mild to moderately dense human breasts. The proposed framework is tested on 3D anatomically accurate numerical breast models and the performance is evaluated across a range of appropriate metrics.

Prefiltered Beamforming for Early-Stage Breast Cancer Detection

Ultrawideband radar imaging has been extensively investigated as a potential alternative to X-ray mammography and has shown promising results in the detection of small tumors within dielectrically homogeneous breast tissue. A range of confocal microwave imaging algorithms has been reported in the literature, showing good tumor detection capabilities, but most of these algorithms suffer significant deterioration in performance with increased amounts of fibro-glandular tissue in the breast. This letter proposes an improved beamformer based on a prefiltering approach to compensate for dispersion and phase effects in a dielectrically heterogeneous breast. The use of prefiltering is shown to improve on conventional beamformer performance and enables detection of multiple scatterers in dense breast tissue. The proposed improved beamformer is tested on 3-D anatomically and dielectrically accurate finite-difference time-domain (FDTD) breast models and the corresponding performance of the beamformer is evaluated across a range of appropriate metrics.

A novel optimized parallelization strategy to accelerate microwave tomography for breast cancer screening.

Microwave tomography has been proven to successfully reconstruct the dielectric profile of a human breast when used in breast imaging applications, thereby providing an alternative to other imaging modalities. However, the method suffers from high computational requirements which restrict its use in practical imaging systems. This paper presents a novel parallelization strategy to accelerate microwave tomography for reconstruction of the dielectric properties of the human breast. A Time Domain algorithm using this parallelization strategy has been validated and benchmarked against an optimized sequential implementation on a conventional high-end desktop Central Processing Unit (CPU), and a comparison of throughput is presented in this paper. The gain in computational throughput is shown to be significantly higher compared with the sequential implementation, ranging from a factor of 26 to 58, on imaging grid sizes of up to 25 cm square at 1mm resolution.

Open-Ended Coaxial Probe Technique for Dielectric Measurement of Biological Tissues: Challenges and Common Practices

Electromagnetic (EM) medical technologies are rapidly expanding worldwide for both diagnostics and therapeutics. As these technologies are low-cost and minimally invasive, they have been the focus of significant research efforts in recent years. Such technologies are often based on the assumption that there is a contrast in the dielectric properties of different tissue types or that the properties of particular tissues fall within a defined range. Thus, accurate knowledge of the dielectric properties of biological tissues is fundamental to EM medical technologies. Over the past decades, numerous studies were conducted to expand the dielectric repository of biological tissues. However, dielectric data is not yet available for every tissue type and at every temperature and frequency. For this reason, dielectric measurements may be performed by researchers who are not specialists in the acquisition of tissue dielectric properties. To this end, this paper reviews the tissue dielectric measurement process performed with an open-ended coaxial probe. Given the high number of factors, including equipment- and tissue-related confounders, that can increase the measurement uncertainty or introduce errors into the tissue dielectric data, this work discusses each step of the coaxial probe measurement procedure, highlighting common practices, challenges, and techniques for controlling and compensating for confounders.

A multistage selective weighting method for improved microwave breast tomography.

Microwave tomography has shown potential to successfully reconstruct the dielectric properties of the human breast, thereby providing an alternative to other imaging modalities used in breast imaging applications. Considering the costly forward solution and complex iterative algorithms, computational complexity becomes a major bottleneck in practical applications of microwave tomography. In addition, the natural tendency of microwave inversion algorithms to reward high contrast breast tissue boundaries, such as the skin-adipose interface, usually leads to a very slow reconstruction of the internal tissue structure of human breast. This paper presents a multistage selective weighting method to improve the reconstruction quality of breast dielectric properties and minimize the computational cost of microwave breast tomography. In the proposed two stage approach, the skin layer is approximated using scaled microwave measurements in the first pass of the inversion algorithm; a numerical skin model is then constructed based on the estimated skin layer and the assumed dielectric properties of the skin tissue. In the second stage of the algorithm, the skin model is used as a priori information to reconstruct the internal tissue structure of the breast using a set of temporal scaling functions. The proposed method is evaluated on anatomically accurate MRI-derived breast phantoms and a comparison with the standard single-stage technique is presented.

Dielectric properties of bones for the monitoring of osteoporosis

AbstractOsteoporosis is one of the most common diseases that leads to bone fractures. Dual-energy X-ray absorptiometry is currently employed to measure the bone mineral density and to diagnose osteoporosis. Alternatively, the dielectric properties of bones are found to be influenced by bone mineral density; hence, dielectric properties of bones may potentially be used to diagnose osteoporosis. Microwave tomographic imaging is currently in development to potentially measure in vivo dielectric properties of bone. Therefore, the foci of this work are to summarize all available dielectric data of bone in the microwave frequency range and to analyze the confounders that may have resulted in variations in reported data. This study also compares the relationship between the dielectric properties and bone quality reported across different studies. The review suggests that variations exist in the dielectric properties of bone and the relationship between bone volume fraction and dielectric properties is in agreement across all studies. Conversely, the evidence of a relationship between bone mineral density and dielectric properties is inconsistent across the studies. This summary of dielectric data of bone along with a comparison of the relationship between the dielectric properties and bone quality will accelerate the development of microwave tomographic imaging devices for the monitoring of osteoporosis. Graphical abstractᅟ

A massively parallel SIMD framework for fast 3D microwave tomography

Microwave Tomography (MT) is one of the most promising emerging imaging modality in recent years, which has shown potential to detect small tumors in human breast. The computational complexity and memory requirement of the MT algorithms are major challenges in further development. This paper presents a Single Instruction Multiple Data (SIMD) framework for fast 3D microwave tomography. A time domain inverse scattering algorithm was used to reconstruct the dielectric properties of human breast. The proposed SIMD framework was evaluated on anatomically accurate numerical breast phantoms, and reconstruction results are presented.

Broadband dielectric properties of adrenal gland for accurate anatomical modelling in medical applications

Dielectric properties of biological tissue are important in safety assessment and evaluation of novel medical imaging and therapeutic devices. This paper reports frequency dependent dielectric properties of adrenal tissue, which is a potential target for microwave ablative therapy to treat benign and malignant adrenal tumors. Dielectric properties of bovine adrenal glands were measured using open-ended coaxial probe over 0.5 to 20 GHz, and a two pole Cole-Cole model was fitted to the measured data. The parameters of Cole-Cole model are presented in this paper.