We introduce a novel wire detection algorithm for use in low altitude urban aircraft reconnaissance. A line profile model is described and effectively used to discriminate wires from other linear patterns commonly fou...
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ISBN:
(纸本)9781424421749
We introduce a novel wire detection algorithm for use in low altitude urban aircraft reconnaissance. A line profile model is described and effectively used to discriminate wires from other linear patterns commonly found in urban scenes. The algorithm is able to cope with highly cluttered backgrounds, moderate rain and mist, and with no stabilization of camera. The studied domain is of particular interest to urban search and rescue and military reconnaissance operations. The algorithmpsilas receiver operating characteristic curve is shown, based on a multi-site dataset with 10160 wires spanning in 5576 frames. Encouraging results show up to 37% detection improvement over a previously published baseline algorithm for comparable false alarm rates.
New bit array pattern and detection algorithm for hard disk drive (HDD) with patterned media are proposed. The width of the reader is larger than a bit width, of which the fabrication cost is lower than a bit-size com...
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New bit array pattern and detection algorithm for hard disk drive (HDD) with patterned media are proposed. The width of the reader is larger than a bit width, of which the fabrication cost is lower than a bit-size compatible reader. It can read several sub-tracks simultaneously, in which the bits are patterned with different phase. The readback signal is superposed by each bit response and we can extract the bit information easily because of its phase difference.
During the past decade, multiple-input-multiple-output (MIMO) systems have received a significant attention because of its promising capacity increase over single-input-single-output (SISO) systems. In this paper, as ...
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ISBN:
(纸本)9784885522321
During the past decade, multiple-input-multiple-output (MIMO) systems have received a significant attention because of its promising capacity increase over single-input-single-output (SISO) systems. In this paper, as a key technology, we present a novel M-paths MIMO detection algorithm with dynamic-layer-ordering for spatial-multiplexing MIMO systems over rich scattering wireless environment. This algorithm obtains a near-ML detection performance (e.g., only 0.2 dB performance degradation for 4-TX and 4-RX MIMO with 16 QAM) with a much lower computational complexity compared to the ML detection. We also develop an recursive procedure for dynamic-layer-ordering and reduce the ordering complexity from O(N T 4 ) to O(N T 3 ), where N T is the number of TX antennas. In order to verify the feasibility and performance, a pipelined structure is designed and implemented in FPGA with limited hardware resources and a 200 Mbps throughput.
In a wireless sensor network, sensors are scattered randomly by aircraft or rocket ejection. On account of scattered randomness, there may be sparse areas of sensors, in which, sensors cannot detect every hole and cor...
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In a wireless sensor network, sensors are scattered randomly by aircraft or rocket ejection. On account of scattered randomness, there may be sparse areas of sensors, in which, sensors cannot detect every hole and corner. Aimed at the region coverage, from another profile, the paper analyses and explains that the randomness of sensor scattered and the limitation of sensor monitor capability lead the appearance of potential traversing path in the whole wireless sensor network, and proposes the potential target traversing detection algorithm based on Voronoi diagram and corresponding solution. Through the analysis of experimental results, the feasibility and the validity of the detection algorithm are proved, and the potential risk can be made up by corresponding solution.
This paper aims at effectively detecting the changes in multi-temporal synthetic aperture radar (SAR) images. Since pixel-based method does not sufficiently utilize the correlation between pixels, it usually may only ...
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This paper aims at effectively detecting the changes in multi-temporal synthetic aperture radar (SAR) images. Since pixel-based method does not sufficiently utilize the correlation between pixels, it usually may only be used in some specific applications. We propose a change detection method that is based upon discrete cosine transform (DCT) classification. It can utilize the correlation between pixels and eliminate unimportant or nuisance forms of changes. It generates a threshold automatically in DCT classification according to the relationship between DCT coefficient and pixel's gray level. In order to eliminate the block effect, we check pixels not only within the target block, but also inside the neighborhood window around the target block. Experimental results show that the proposed method outperforms some recently published pixel-based methods.
Nowadays, millions of people's living and work habits are affected by TV commercials. A feature-based real-time TV commercial detection algorithm is proposed in this work. In terms of the combination of the visual...
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Nowadays, millions of people's living and work habits are affected by TV commercials. A feature-based real-time TV commercial detection algorithm is proposed in this work. In terms of the combination of the visual and acoustic features, and the temporal information, we detect the end and the start boundary of the commercial separately. Then, in order to refine the detecting result further, we address a set of basic features that is easy to distinguish the commercial from general programs. Based on these features, a finite automation is build simultaneously, which well illustrates our detection method clearly. The experimental results show that our algorithm can yield better recall (96.47%) and precision (97.27%) by comparing with current main approaches.
In this paper we propose a novel technique for detecting rotation and scale invariant interest points from the local frequency representation of an image. Local or instantaneous frequency is the spatial derivative of ...
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In this paper we propose a novel technique for detecting rotation and scale invariant interest points from the local frequency representation of an image. Local or instantaneous frequency is the spatial derivative of the local phase, where the local phase of any signal can be found from its Hilbert transform. Local frequency estimation can detect edge, ridge, corner and texture information at the same time and shows high values at those dominant features of an image. For each pixel, we select an appropriate width of the window for computing the derivative of the phase. In order to select the width of the window for any given pixel, we make use of the measure of the extent to which the phases, in the neighborhood of that pixel, are in the same direction. The local frequency map, thus obtained, is then thresholded by employing a global thresholding approach to detect the interest or feature points. Repeatability rate, a performance evaluation criterion for an interest points detector, is used to check the geometric stability of the proposed method under different transformations. We present simulation results of the detection of feature points from an image and the repeatability rate as a function of image rotation and scale changes. The results prove the efficacy of the proposed feature points detection algorithm.
In the paper a problem of analyzing surgeon's right hand wrist trajectory during laparoscopic operation is considered. Based on the results of the analysis detection algorithms to recognize six motions are develop...
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In the paper a problem of analyzing surgeon's right hand wrist trajectory during laparoscopic operation is considered. Based on the results of the analysis detection algorithms to recognize six motions are developed. The motions can be considered as primitives of a surgery from the human scrub nurse point of view. In the analysis, to represent motions the third order polynomials are used. The two proposed algorithms are based on Kohonen maps and boosted decision trees. The performance of the algorithms is tested on surgical operation data.
In communication environments such as power line channel, impulsive noise greatly deteriorates the performance of detection algorithm based on Gauss optimization. This paper introduces a symmetric alpha stable (Salpha...
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In communication environments such as power line channel, impulsive noise greatly deteriorates the performance of detection algorithm based on Gauss optimization. This paper introduces a symmetric alpha stable (SalphaS) distribution to model a statistical model of impulsive noise, and considers that interference in the receiver is a mixture of additional white Gaussian noise (AWGN) and SalphaS noise. Based on this noise model, a nonlinear detector is proposed through the numerical calculation method. Simulations show that the proposed detector is robust, and its performance is slightly worse than the locally optimum (LO) in non-Gaussian environment, however, the key parameters do not need known in advance and its computational complexity is reduced greatly.
In many application suck as face detection or recognition a major phase would be eye detection. In addition, its wide use as a part of serious applications, made it an important task should be worked on. Using color c...
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In many application suck as face detection or recognition a major phase would be eye detection. In addition, its wide use as a part of serious applications, made it an important task should be worked on. Using color characteristics is a useful way to detect eyes. We use special color space, YCbCr which its components give us worthwhile information about eyes. We make two maps according to its components and merge them to obtain a final map. Candidates are generated on this final map. We apply an extra phase on candidates to determine suitable eye pair. The extra phase consists of flexible thresholding and geometrical tests. Flexible thresholding makes generating candidates more carefully and geometrical tests allow proper candidates to be selected as eyes. Simulation results on CVI and Iranian Databases showed this phase improved the correct detection rate by about 12.4% and reach 98.5% success rate on the average.
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