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Full-Text Articles in Engineering
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 …
Reference-Free Differential Histogram-Correlative Detection Of Steganography: Performance Analysis, Natiq M. Abdali, Zahir M. Hussain
Reference-Free Differential Histogram-Correlative Detection Of Steganography: Performance Analysis, Natiq M. Abdali, Zahir M. Hussain
Research outputs 2022 to 2026
Recent research has demonstrated the effectiveness of utilizing neural networks for detect tampering in images. However, because accessing a database is complex, which is needed in the classification process to detect tampering, reference-free steganalysis attracted attention. In recent work, an approach for least significant bit (LSB) steganalysis has been presented based on analyzing the derivatives of the histogram correlation. In this paper, we further examine this strategy for other steganographic methods. Detecting image tampering in the spatial domain, such as image steganography. It is found that the above approach could be applied successfully to other kinds of steganography with different …
Measurement Of Micro Burr And Slot Widths Through Image Processing: Comparison Of Manual And Automated Measurements In Micro‐Milling, Fatih Akkoyun, Ali Ercetin, Kubilay Aslantas, Danil Yurievich Pimenov, Khaled Giasin, Avinash Lakshmikanthan, Muhammad Aamir
Measurement Of Micro Burr And Slot Widths Through Image Processing: Comparison Of Manual And Automated Measurements In Micro‐Milling, Fatih Akkoyun, Ali Ercetin, Kubilay Aslantas, Danil Yurievich Pimenov, Khaled Giasin, Avinash Lakshmikanthan, Muhammad Aamir
Research outputs 2014 to 2021
In this study, the burr and slot widths formed after the micro‐milling process of Inconel 718 alloy were investigated using a rapid and accurate image processing method. The measurements were obtained using a user‐defined subroutine for image processing. To determine the accuracy of the developed imaging process technique, the automated measurement results were compared against results measured using a manual measurement method. For the cutting experiments, Inconel 718 alloy was machined using several cutting tools with different geometry, such as the helix angle, axial rake angle, and number of cutting edges. The images of the burr and slots were captured …
A Statistical Approach To Provide Explainable Convolutional Neural Network Parameter Optimization, Saman Akbarzadeh, Selam Ahderom, Kamal Alameh
A Statistical Approach To Provide Explainable Convolutional Neural Network Parameter Optimization, Saman Akbarzadeh, Selam Ahderom, Kamal Alameh
Research outputs 2014 to 2021
Algorithms based on convolutional neural networks (CNNs) have been great attention in image processing due to their ability to find patterns and recognize objects in a wide range of scientific and industrial applications. Finding the best network and optimizing its hyperparameters for a specific application are central challenges for CNNs. Most state-of-the-art CNNs are manually designed, while techniques for automatically finding the best architecture and hyperparameters are computationally intensive, and hence, there is a need to severely limit their search space. This paper proposes a fast statistical method for CNN parameter optimization, which can be applied in many CNN applications …
Simulation Of A Mobile Robot Navigation System, Ahmed Khusheef, Ganesh Kothapalli, Majid Tolouei Rad
Simulation Of A Mobile Robot Navigation System, Ahmed Khusheef, Ganesh Kothapalli, Majid Tolouei Rad
Research outputs 2011
Mobile robots are used in various application areas including manufacturing, mining, military operations, search and rescue missions and so on. As such there is a need to model robot mobility that tracks robot system modules such as navigation system and visi on based object recognition. For the navigation system it is important to locate the position of the robot in surr ounding environment. Then it has to plan a path towards desired destination. The navigation system of a robot has to identify all potential obstacles in order to find a suitable path. The objective of this research is to develop …
Jpeg Compression Of Monochrome 2d-Barcode Images Using Dct Coefficient Distributions, Keng Teong Tan, Douglas Chai
Jpeg Compression Of Monochrome 2d-Barcode Images Using Dct Coefficient Distributions, Keng Teong Tan, Douglas Chai
Research outputs pre 2011
Two dimensional (2D) barcodes are becoming a pervasive interface for mobile devices, such as camera phones. Often, only monochrome 2D-barcodes are used due to their robustness in an uncontrolled operating environment of camera phones. Most camera phones capture and store such 2D-barcode images in the baseline JPEG format. As a lossy compression technique, JPEG does introduce a fair amount of error in the decoding of captured 2D-barcode images. In this paper, we introduce an improved JPEG compression scheme for such barcode images. By altering the JPEG compression parameters based on the DCT coefficient distribution of such barcode images, the improved …
Firearm Forensics Based On Ballistics Cartridge Case Image Segmentation Using Colour Invariants, Dongguang Li
Firearm Forensics Based On Ballistics Cartridge Case Image Segmentation Using Colour Invariants, Dongguang Li
Australian Security and Intelligence Conference
Ballistics firearm identification based on image processing is of paramount importance in criminal investigation. The efficiency of traditional ballistics imaging system is heavily dependent upon the expertise and experience of end-user. An intelligent ballistics imaging system is highly demanded to address this issues. The segmentation of cartridge case object from the original image is a key step to subsequent process. It is very difficult to segment cartridge case from the original image using traditional threshold based methods due to the shadows or unlimited environments to acquire image. In this paper, we proposed a novel approach based upon the colour invariant …