• Parasites, Hosts and Diseases
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• v.47 no.3
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• pp.293-297
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• 2009

Improved methods for detection of Cryptosporidium oocysts in environmental and clinical samples are urgently needed to improve detection of cryptosporidiosis. We compared the sensitivity of 7 PCR primer sets for detection of Cryptosporidium parvum. Each target gene was amplified by PCR or nested PCR with serially diluted DNA extracted from purified C. parvum oocysts. The target genes included Cryptosporidium oocyst wall protein (COWP), small subunit ribosomal RNA (SSU rRNA), and random amplified polymorphic DNA. The detection limit of the PCR method ranged from $10^3$ to $10^4$ oocysts, and the nested PCR method was able to detect $10^0$ to $10^2$ oocysts. A second-round amplification of target genes showed that the nested primer set specific for the COWP gene proved to be the most sensitive one compared to the other primer sets tested in this study and would therefore be useful for the detection of C. parvum.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.272-287
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• 2016

Recently, various and effective contrast based salient object detection models to focus on a single target have been proposed. However, there is a lack of research on detection of multiple objects, and also it is a more challenging task than single target process. In the multiple target problem, we are confronted by new difficulties caused by distinct difference between properties of objects. The characteristic of existing models depending on the global maximum distribution of data point would become a drawback for detection of multiple objects. In this paper, by analyzing limitations of the existing methods, we have devised three main processes to detect multiple salient objects. In the first stage, regional features are extracted from over-segmented regions. In the second stage, the regional features are categorized into homogeneous cluster using the mean-shift algorithm with the kernel function having various sizes. In the final stage, we compute saliency scores of the categorized regions using only spatial features without the contrast features, and then all scores are integrated for the final salient regions. In the experimental results, the scheme achieved superior detection accuracy for the SED2 and MSRA-ASD benchmarks with both a higher precision and better recall than state-of-the-art approaches. Especially, given multiple objects having different properties, our model significantly outperforms all existing models.

• Journal of Advanced Navigation Technology
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• v.6 no.3
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• pp.231-240
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• 2002

For a long time target maneuvers in tracking problem have been a difficult task to handle. In order to solve this problems. there have been various tracking techniques. In the development of a tracking filter for a maneuvering target, maneuver detection threshold plays a key role. However, no study of filter performance the varying maneuver detection threshold has been carried out so far. Instead, the maneuver detection have been chosen empirically. In this paper, the effect of detection threshold selection on the performance of the tracking filters was considered and the relationships between maneuvers and the detection threshold have been analyzed by simulation.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.5
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• pp.708-716
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• 2017

We deal with the target selection in seeker-detection image through network, using the detection information from aerial vehicle and the target information from surveillance and reconnaissance system. Especially, we constrain the sea battle environment, where it is difficult to perform scene-matching rather than land. In this paper, we suggest the target selection algorithm based on the confidence estimation with respect to distance and size. In detail, we propose the generation method of reference point for distance evaluation, and we investigate the effect of pixel margin and target course for size evaluation. Finally, the proposed algorithm is simulated and analyzed through several scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1173-1192
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• 2015

The Support Vector Data Description (SVDD) has achieved great success in anomaly detection, directly finding the optimal ball with a minimal radius and center, which contains most of the target data. The SVDD has some limited classification capability, because the hyper-sphere, even in feature space, can express only a limited region of the target class. This paper presents an anomaly detection algorithm for mitigating the limitations of the conventional SVDD by finding the minimum volume enclosing ellipsoid in the feature space. To evaluate the performance of the proposed approach, we tested it with intrusion detection applications. Experimental results show the prominence of the proposed approach for anomaly detection compared with the standard SVDD.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.107-112
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• 2014

In this paper, we analysed a performance signal to noise ratio about pulse, integration coherent, and integration non coherent system in radar system. It compared existing with proposal method in order to estimation two target direction of arrival. Generally, radar system radiate pulse wave in order to decreasing distortion of return wave and transmission wave. We analysed the performance integration coherent and integration non coherent. Integration coherent is processing system before doing envelop detection, and integration non coherent is processing system after doing envelop detection. Through simulation, we analysed a performance signal to noise ratio to estimation two target range detection and estimated target direction of arrival. We showed that integration coherent system is the most good performance.

• MALSORI
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• no.59
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• pp.27-51
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• 2006

For speech recognition systems, rejection function as well as decoding function is necessary to improve the reliability. There have been many research efforts on out-of-vocabulary word rejection, however, little attention has been paid on non-target sentence rejection. Recently pronunciation approaches using speech recognition increase the need for non-target sentence rejection to provide more accurate and robust results. In this paper, we proposed filler model method and word/phoneme detection ratio method to implement non-target sentence rejection system. We made performance evaluation of filler model along to word-level, phoneme-level, and sentence-level filler models respectively. We also perform the similar experiment using word-level and phoneme-level word/phoneme detection ratio method. For the performance evaluation, the minimized average of FAR and FRR is used for comparing the effectiveness of each method along with the number of words of given sentences. From the experimental results, we got to know that word-level method outperforms the other methods, and word-level filler mode shows slightly better results than that of word detection ratio method.

• Journal of the Korea Society of Computer and Information
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• v.8 no.2
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• pp.31-36
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• 2003

This paper proposes an acceleration method of PCA(Principal Component Analysis) based feature detection. The feature detection method makes decision whether the target feature is included in a given image, and if included, calculates the position and extent of the target feature. The position and scale of the target feature or face is not known previously, all the possible locations should be tested for various scales to detect the target. This is a search Problem in huge search space. This Paper proposes a fast face and feature detection method by reducing the search space using the multi-stage prediction map and contour Prediction map. A Proposed method compared to the existing whole search way, and it was able to reduce a computational complexity below 10％ by experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.976-983
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• 2002

We presents a modified variable dimension filter with input estimation for maneuvering target tracking. The conventional variable dimension filter with input estimation(VDIE) consists of the input estimation(IE) technique and the variable dimension(VD) filter. In the VDIE, the IE technique is used for estimation of a maneuver onset time and its magnitude in the least square sense. The detection of the maneuver is declared according to the estimated magnitude of the maneuver. The VD filter structure is applied for the adaptation to the maneuver of the target after compensating the filter parameter with respect to the estimated maneuver when the detection of the maneuver is declared. The VDIE is known as one of the best maneuvering target tracking filter based on a single filter. However, it requires too much computational burden since the IE technique is performed at every sampling instance and thus it is computationally inefficient. We propose another variable dimension filter with input estimation named 'Modified VDIE' which combines VD filter with If technique. Modified VDIE has less computational load than the original one by separating maneuver detection and input estimation. Simulation results show that the proposed VDIE is more efficient and outperforms in terms of computational load.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.699-701
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• 2017

Typical operating method for long-range observation cameras are to detect the target at a wide angle of view and to recognize/identify the target with a telephoto angle of view. And the detection/recognition range performance is an important item to evaluate the performance of the defense infrared camera. To increased the detection range performance, the camera's field of view should be narrowed. Due to the narrow field of view, the probability of finding target is relatively low. In this paper, we propose a method to search for target by providing a wide angle view while maintaining detection range performance. M&S and optimized design were used to develop infrared camera with extended field of view and the results of the test summarized.