M. R. Arshad

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This paper proposes a method for recognition and classification of 3D objects using 2D moments and HMLP network. The 2D moments are calculated based on 2D intensity images taken from multiple cameras that have been arranged using multiple views technique. 2D moments are commonly used for 2D pattern recognition. However, the current study proves that with(More)
This paper presents an initial development stage of Fly Optimization Algorithm which will be used for the path planning system of a swarm of autonomous surface vehicles. This algorithm was initially designed to be implemented for a swarm of robots which would be able to locate the deepest portion of lakes. The ability of the robots to reach the designated(More)
This paper addresses a performance analysis of two well known moments, namely Hu's moments and Zernike's moments for 3D object recognition. Hu's moments and Zernike's moments are the non-orthogonal and orthogonal moments respectively, which are commonly used as shape feature for 2D object or pattern recognition. The current study proved that with some(More)
This paper presents the initial developmental stage of mini Autonomous Surface Vehicles (ASVs), which is to define the algorithm of boundary navigation for each of the ASV via programming and sensor networks. To implement this, region recognition and several path planning algorithms have been utilized. Besides that, pixilation of path is also used to(More)
This paper proposes an effective method for recognition and classification of 3D objects using multiple views technique and neural networks system. In the processing stage, we propose to use 2D moment invariants as the features for modeling 3D objects. 2D moments have been commonly used for 2D object recognition. However, we have proved that with some(More)
The aim of this research effort is to build a robust image-based virtual input for robotic platform control. Compared to the motion of the head, eye gaze, face or even the whole body, tracking of hand movement has become increasingly popular, efficient and more natural in human computer interaction. However available systems are invasive and require the(More)
Autonomous underwater vehicle can perform underwater docking to power up its battery in order to prolong operation thereby reduces maintenance and cost. Prior researches indicate visual servo technique is used for docking operation. Basically, image of markers placed on underwater station is captured and the vehicle surges towards the station. These(More)
Shorelines and water surface recognition are fundamental cues for ASV navigating in a river. In this paper we present an adaptive shorelines detection approach which is combination of feature-based and edge based method. Firstly, the river boundary is extracted adaptively by color segmentation with a sampling patch. Secondly, the river boundary constrained(More)
Underwater acoustic source localization is important in many underwater applications. However, due to the intensity degradation of acoustic signal as the distance from the source increases, the possibility to detect and localize the source using a single surface platform become harder. This paper presents an underwater acoustic source localization strategy(More)
This paper presents a three-dimensional virtual registration for human motion analysis. We will focus on constructing 3D visualization of human body from different views of the cameras. The 3D representation then can be used for medical diagnosis such as for evaluation and analysis for people who have walking difficulties and require rehabilitation therapy.(More)