Wei Yeang Kow

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Image segmentation with low computational burden has been highly regarded as important goal for researchers. Various image segmentation methods are widely discussed and more noble segmentation methods are expected to be developed when there is rapid demand from the emerging machine vision field. One of the popular image segmentation methods is by using(More)
Image segmentation has been widely applied in image analysis for various areas such as biomedical imaging, intelligent transportation systems and satellite imaging. The main goal of image segmentation is to simplify an image into segments that have a strong correlation with objects in the real world. Homogeneous regions of an image are regions containing(More)
Vehicle detection and tracking is essential in traffic surveillance and traffic flow optimization. However, occlusion or overlapped vehicle tracking is difficult and remain a challenging research topic in image processing. In this paper, a conventional Markov Chain Monte Carlo (MCMC) is enhanced via Cumulative Sum (CUSUM) path plot in order to track(More)
Nowadays, vehicle tracking is a vital approach to assist and improve the road traffic control, surveillance and security systems by having the detail of the captured vehicle information. In past, many tracking techniques have been implemented and suffered from the well known 'occlusion' problems. Increasing the accuracy of the tracking algorithm has caused(More)
One of the critical tasks in object tracking is the tracking of fast-moving object in random motion, especially in the field of machine vision applications. An approach towards the hybrid of particle filter (PF) and mean shift (MS) algorithm in visual tracking is proposed. In this proposed system, complete occlusion and random movement of object can be(More)
Traffic flow optimization within traffic networks has been approached through different kinds of methods. One of the methods is to reconfigure the traffic signal timing plan. However, dynamic characteristic of the traffic flow is not able to be resolved by the conventional traffic signal timing plan management. As a result, traffic congestion still remains(More)
Vehicle tracking is a vital approach to assist the on-road traffic surveillance system. Since the on-road vehicles is increasing, occlusion and overlapping of vehicles is often happen in the traffic surveillance scene. Therefore, segmentation and tracking of the occlusion or overlapped vehicle can be a challenging task in surveillance system via image(More)
Traffic surveillance and on-road security have elevated the demand of machine vision aided traffic control system. Through the modern video camera technology, vehicle tracking has become a vital approach to assist the on-road traffic systems. In the past, many tracking methods have been developed based on the detail and information extracted from the(More)
Pictures are considered as a standout amongst the most imperative medium of passing on information. Understanding pictures and separating the data from them such that the data can be utilized for different undertakings is a critical part of Machine learning. Picture division is the methodology of separating the given picture into districts in light of a few(More)
Optical sensors based vehicle tracking can be widely implemented in traffic surveillance and flow control. The vast development of video surveillance infrastructure in recent years has drawn the current research focus towards vehicle tracking using high-end and low cost optical sensors. However, tracking vehicles via such sensors could be challenging due to(More)