5 research outputs found

    Thresholding and quantization algorithms for image compression techniques: a review

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    With increasing demand on digital images, there is a need to compress the image to entertain the limited bandwidth and storage capacity. Recently, there is a growing interest among researchers focusing on compression of various types of images and data. Amongst various compression algorithms, transform-based compression is one of the promising algorithms. Despite the technological advances in transmission and storage, the demands placed on the bandwidth of communication and storage capacities by far outstrips its availability. This paper presents a review of image compression principle, compression techniques and various thresholding algorithms (pre-processing algorithms) and quantization algorithm (post-processing algorithms). This paper intends to give an overview to the relevant parties to choose the suitable image compression algorithms to suit with the need

    An RFID warehouse robot

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    RFID is one of the latest trend in the industry. Its potential application can range from warehouse to library management. This project is aimed to build an autonomous robot with RFID application. The project integrates RFID reader and PIC microcontroller as the main components. The movement control comprises servo-motor with infrared sensors for the line follower. The whole programming operation was carried out by assembly language using MPLab 7.3. The robot has the ability to identify the items by reading the tag on the items. The robot will pick up the item and navigate to prescribed destination using line follower module to store the item at the appropriate place and location. A small white platform with black line is built for demonstration and testing

    Secured MyVirtualPDA using advanced encryption standard

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    One of the most useful features in any personal digital assistant (PDA) is that it can accumulate information needed including easy-to-forget details. Some of the information stored is likely to be very sensitive including credit card numbers, personal identification, and passwords. To protect this sensitive data, most PDAs offer password protection as a basic authentication. However, to rely on this type of protection alone is not enough. As the writing of secret message cryptography, also known as science and mathematical lock and key (Schafer, 2003), evolved people rely on the encryption process to increase their level of data protection

    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data

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    Feature Selection in High Dimensional Space is a combinatory optimization problem with an NP-hard nature. Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. However, the increase in the dimension of the solution space leads to a high computational cost and risk of convergence. In addition, sub-optimality might occur due to the assumption of a certain length of the optimal number of features. Alternatively, variable length searching enables searching within the variable length of the solution space, which leads to more optimality and less computational load. The literature contains various meta-heuristic algorithms with variable length searching. All of them enable searching in high dimensional problems. However, an uncertainty in their performance exists. In order to fill this gap, this article proposes a novel framework for comparing various variants of variable length-searching meta-heuristic algorithms in the application of feature selection. For this purpose, we implemented four types of variable length meta-heuristic searching algorithms, namely VLBHO-Fitness, VLBHO-Position, variable length particle swarm optimization (VLPSO) and genetic variable length (GAVL), and we compared them in terms of classification metrics. The evaluation showed the overall superiority of VLBHO over the other algorithms in terms of accomplishing lower fitness values when optimizing mathematical functions of the variable length type
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