Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
- Publication
- Publication Type
Articles 1 - 11 of 11
Full-Text Articles in Physical Sciences and Mathematics
Enhancing Water Safety: Exploring Recent Technological Approaches For Drowning Detection, Salman Jalalifar, Andrew Belford, Eila Erfani, Amir Razmjou, Rouzbeh Abbassi, Masoud Mohseni-Dargah, Mohsen Asadnia
Enhancing Water Safety: Exploring Recent Technological Approaches For Drowning Detection, Salman Jalalifar, Andrew Belford, Eila Erfani, Amir Razmjou, Rouzbeh Abbassi, Masoud Mohseni-Dargah, Mohsen Asadnia
Research outputs 2022 to 2026
Drowning poses a significant threat, resulting in unexpected injuries and fatalities. To promote water sports activities, it is crucial to develop surveillance systems that enhance safety around pools and waterways. This paper presents an overview of recent advancements in drowning detection, with a specific focus on image processing and sensor-based methods. Furthermore, the potential of artificial intelligence (AI), machine learning algorithms (MLAs), and robotics technology in this field is explored. The review examines the technological challenges, benefits, and drawbacks associated with these approaches. The findings reveal that image processing and sensor-based technologies are the most effective approaches for drowning detection …
Design Of A Hybrid Measure For Image Similarity: A Statistical, Algebraic, And Information-Theoretic Approach, Mohammed Abdulameer Aljanabi, Zahir M. Hussain, Noor Abd Alrazak Shnain, Song Feng Lu
Design Of A Hybrid Measure For Image Similarity: A Statistical, Algebraic, And Information-Theoretic Approach, Mohammed Abdulameer Aljanabi, Zahir M. Hussain, Noor Abd Alrazak Shnain, Song Feng Lu
Research outputs 2014 to 2021
Image similarity or distortion assessment is fundamental to a wide range of applications throughout the field of image processing and computer vision. Many image similarity measures have been proposed to treat specific types of image distortions. Most of these measures are based on statistical approaches, such as the classic SSIM. In this paper, we present a different approach by interpolating the information theory with the statistic, because the information theory has a high capability to predict the relationship among image intensity values. Our unique hybrid approach incorporates information theory (Shannon entropy) with a statistic (SSIM), as well as a distinctive …
Text Extraction In Natural Scenes Using Region-Based Method, Zhihu Huang, Jinsong Leng
Text Extraction In Natural Scenes Using Region-Based Method, Zhihu Huang, Jinsong Leng
Research outputs 2014 to 2021
Text in images is a very important clue for image indexing and retrieving. Unfortunately, it is a challenging work to accurately and robustly extract text from a complex background image. In this paper, a novel region-based text extraction method is proposed. In doing so, the candidate text regions are detected by 8-connected objects detection algorithm based on the edge image. Then the non-text regions are filtered out using shape, texture and stroke width rules. Finally, the remaining regions are grouped into text lines. Since stroke width is the intrinsic and particular characteristics of the text, the accuracy of the non-text …
An Information-Theoretic Image Quality Measure: Comparison With Statistical Similarity, Asmhan F. Hassan, Dong Cailin, Zahir M. Hussain
An Information-Theoretic Image Quality Measure: Comparison With Statistical Similarity, Asmhan F. Hassan, Dong Cailin, Zahir M. Hussain
Research outputs 2014 to 2021
We present an information-theoretic approach for structural similarity for assessing gray scale image quality. The structural similarity measure SSIM, proposed in 2004, has been successflly used and verfied. SSIM is based on statistical similarity between the two images. However, SSIM can produce confusing results in some cases where it may give a non-trivial amount of similarity for two different images. Also, SSIM cannot perform well (in detecting similarity or dissimilarity) at low peak signal to noise ratio (PSNR). In this study, we present a novel image similarity measure, HSSIM, by using information - theoretic technique based on joint histogram. The …
A Survey Of Image Processing Techniques For Agriculture, Lalit Saxena, Leisa Armstrong
A Survey Of Image Processing Techniques For Agriculture, Lalit Saxena, Leisa Armstrong
Research outputs 2014 to 2021
Computer technologies have been shown to improve agricultural productivity in a number of ways. One technique which is emerging as a useful tool is image processing. This paper presents a short survey on using image processing techniques to assist researchers and farmers to improve agricultural practices. Image processing has been used to assist with precision agriculture practices, weed and herbicide technologies, monitoring plant growth and plant nutrition management. This paper highlights the future potential for image processing for different agricultural industry contexts.
A Novel Binarization Algorithm For Ballistics Imaging Systems, Zhihu Huang, Jinsong Leng
A Novel Binarization Algorithm For Ballistics Imaging Systems, Zhihu Huang, Jinsong Leng
Research outputs pre 2011
The identification of ballistics specimens from imaging systems is of paramount importance in criminal investigation. Binarization plays a key role in preprocess of recognizing cartridges in the ballistic imaging systems. Unfortunately, it is very difficult to get the satisfactory binary image using existing binary algorithms. In this paper, we utilize the global and local thresholds to enhance the image binarization. Importantly, we present a novel criterion for effectively detecting edges in the images. Comprehensive experiments have been conducted over sample ballistic images. The empirical results demonstrate the proposed method can provide a better solution than existing binary algorithms.
Ballistics Image Processing And Analysis For Firearm Identification, Dongguang Li
Ballistics Image Processing And Analysis For Firearm Identification, Dongguang Li
Research outputs pre 2011
Firearm identification is an intensive and time-consuming process that requires physical interpretation of forensic ballistics evidence. Especially as the level of violent crime involving firearms escalates, the number of firearms to be identified accumulates dramatically. The demand for an automatic firearm identification system arises. This chapter proposes a new, analytic system for automatic firearm identification based on the cartridge and projectile specimens. Not only do we present an approach for capturing and storing the surface image of the spent projectiles at high resolution using line-scan imaging technique for the projectiles database, but we also present a novel and effective FFT-based …
Contrast Enhancement Of Ultrasound Images Using Shunting Inhibitory Cellular Neural Networks, Murali M. Gogineni
Contrast Enhancement Of Ultrasound Images Using Shunting Inhibitory Cellular Neural Networks, Murali M. Gogineni
Theses: Doctorates and Masters
Evolving from neuro-biological insights, neural network technology gives a computer system an amazing capacity to actually generate decisions dynamically. However, as the amount of data to be processed increases, there is a demand for developing new types of networks such as Cellular Neural Networks (CNN), to ease the computational burden without compromising the outcomes. The objective of this thesis is to research the capability of Shunting Inhibitory Cellular Neural Networks (SICNN) to solve the clarity problems in ultrasound imaging. In this thesis, we begin by reviewing a number of traditional enhancement techniques and measures. Since the entire work of this …
Use Of Multi-Scale Phase-Based Methods To Determine Optical Flow In Dynamic Scene Analysis, Robert Hastings
Use Of Multi-Scale Phase-Based Methods To Determine Optical Flow In Dynamic Scene Analysis, Robert Hastings
Theses: Doctorates and Masters
Estimates of optical flow in images can be made by applying a complex periodic transform to the images and tracking the movement of points of constant phase in the complex output. This approach however suffers from the problem that filters of large width give information only about broad scale image features, whilst those of small spatial extent (high resolution) cannot track fast motion, which causes a feature to move a distance that is large compared to the filter-size. A method is presented in which the flow is measured at different scales, using a series of complex filters of decreasing width. …
Depth-First Search Embedded Wavelet Algorithm For Hardware Implementation, Li-Minn Ang
Depth-First Search Embedded Wavelet Algorithm For Hardware Implementation, Li-Minn Ang
Theses: Doctorates and Masters
The emerging technology of image communication over wireless transmission channels requires several new challenges to be simultaneously met at the algorithm and architecture levels. At the algorithm level, desirable features include high coding performance, bit stream scalability, robustness to transmission errors and suitability for content-based coding schemes. At the architecture level, we require efficient architectures for construction of portable devices with small size and low power consumption. An important question is to ask if a single coding algorithm can be designed to meet the diverse requirements. Recently, researchers working on improving different features have converged on a set of coding …
Sicnn Optimisation, Two Dimensional Implementation And Comparison, Grant Walker
Sicnn Optimisation, Two Dimensional Implementation And Comparison, Grant Walker
Theses : Honours
The study investigates the process of optimisation, implementation and comparison of a Shunting Inhibitory Cellular Neural Network (SICNN) for Edge Detection. Shunting inhibition is lateral inhibition where the inhibition function is nonlinear. Cellular Neural Networks are locally interconnected nonlinear, parallel networks which can exist as either discrete time or continuous networks. The name given to Cellular Neural Networks that use shunting inhibition as their nonlinear cell interactions are called Shunting Inhibitory Cellular Neural Networks. This project report examines some existing edge detectors and thresholding techniques. Then it describes the optimisation of the connection weight matrix for SICNN with Complementary Output …