For image matching, the scale invariant feature transform (SIFT) algorithm is a commonly used one. They are invariant to image rotation, scale zooming, and partially invariant to change in illumination and 3D camera v...
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For image matching, the scale invariant feature transform (SIFT) algorithm is a commonly used one. They are invariant to image rotation, scale zooming, and partially invariant to change in illumination and 3D camera viewpoint. Affine SIFT (ASIFT) is an extension of SIFT, which solves the problem when images are captured at different angles. However, ASIFT has higher computational complexity than SIFT, due to a huge amount of features in the images. Therefore, in this study, a Hadoop-based image retrieval system is proposed to solve the ASIFT shortcomings of high computation by the MapReduce technology. The system uses a combination of the Bag-of-Words method and support vector machine. Finally, the experimental results verify that the proposed method is more effective than the other state-of-the-art methods for a variety of datasets.
Partial transmit sequence (PTS) is one of the effective techniques for reducing the peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. PTS technique has some issues such a...
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Partial transmit sequence (PTS) is one of the effective techniques for reducing the peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. PTS technique has some issues such as higher computational complexity due to its exhaustive searching of optimal phase factors. In order to overcome this drawback, a scaled particle swarm optimisation algorithm is applied to PTS technique to find the optimal phase factors for reducing the PAPR at a faster convergence rate and lower computationalcomplexity. A scaling factor has been introduced in the velocity updating equation of conventional particle swarm optimisation (PSO) to increase the inertia weight and velocity of the particle, thereby providing faster convergence to the optimum value as well as reducing PAPR effectively. From the simulation results obtained, it can be observed that the proposed scaled PSO-PTS algorithm reduces PAPR effectively and is most suitable for applications with the 64-QAM modulation scheme.
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