• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.275-279
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• 2002

Change Detection is a useful technology that can be applied to various fields, taking temporal change information with the comparison and analysis among multi-temporal satellite images. Especially, Change Detection that utilizes high-resolution satellite imagery can be implemented to extract useful change information for many purposes, such as the environmental inspection, the circumstantial analysis of disaster damage, the inspection of illegal building, and the military use, which cannot be achieved by low- or middle-resolution satellite imagery. However, because of the special characteristics that result from high-resolution satellite imagery, it cannot use a pixel-based method that is used for low-resolution satellite imagery. Therefore, it must be used a feature-based algorithm based on the geographical and morphological feature. This paper presents the system that builds the change map by digitizing the boundary of the changed object. In this system, we can make the change map using manual or semi-automatic digitizing through the user interface implemented with a floating window that enables to detect the sign of the change, such as the construction or dismantlement, more efficiently.

• Ocean and Polar Research
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• v.39 no.2
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• pp.73-84
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• 2017

The probability distribution of ichthyoplankton is important for enhancing the precision of sampling while reducing unnecessary surveys. To estimate the ichthyoplankton detection proportion (IDP) and its margin of error (ME), the monitoring information of the chub mackerel's (Scomber japonicus) ichthyoplankton presence-absence sampling data has been were collected over approximately 30 years (from 1982 to 2011) in the Korean coastal seas. Based on the computed spatial distributions of the mackerel's IDP and ME, the confidence interval (CI) range, defined as 2 ME, decreases from approximately 80% to 40% as the sample size n increases from 4 to 24 and the ME is approximately 40% in the typical (seasonal survey) case n = 4 per year. The IDP and ME off Jeju Island are relatively high at the 0.5-degree smoothing level. After increasing the spatial smoothing level to 1.0-degree, the ME decreased, and the spatial distribution pattern also changed due to the over-smoothing effects. In this study, the 0.5-degree smoothing is more suitable for the distribution pattern than the 1.0-degree smoothing level. The area of the high IDP and the low ME on the mackerel's ichthyoplankton was similar to the estimated spawning ground in the Korean peninsula. This information could contribute to enhancing for the spawning ecology surveys.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.61-66
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• 2013

In this paper, we propose an iterative soft dimension reduction based multi-input multi-output (MIMO) detection for coded spatial multiplexing system. In spite of better performance of iterative MIMO detection, its computational complexity gives a significant burden to the receivers. To mitigate this problem, we propose a scheme employing all ordering successive interference cancellation (AOSIC) for hard-decision detection and dimension reduction soft demodulator (DRSD) with iterative decoding for soft-decision detectors, respectively. This scheme can reduce complexity of iterative soft MIMO detection and provide better performance than other conventional detectors.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.11
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• pp.1044-1052
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• 2010

In this paper, a new realtime algorithm called the RTPBTD-HPDAF (Recursive Temporal Profile Base Target Detection with Highest Probability Data Association Filter) is presented for tracking fast moving small targets with IIR (Imaging Infrared) sensor systems. Spatial filter algorithms are mainly used for target in IIR sensor system detection and tracking however they often generate high density clutter due to various shapes of cloud. The TPBTD (Temporal Profile Base Target Detection) algorithm based on the analysis of temporal behavior of individual pixels is known to have good performance for detection and tracking of fast moving target with suppressing clutter. However it is not suitable to detect stationary and abruptly maneuvering targets. Moreover its computational load may not be negligible. The PTPBTD-HPDAF algorithm proposed in this paper for real-time target detection and tracking is shown to be computationally cheap while it has benefit of tracking targets with abrupt maneuvers. The performance of the proposed RTPBTD-HPDAF algorithm is tested and compared with the spatial filter with HPDAF algorithm for run-time and track initiation at real IIR video.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.5
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• pp.439-444
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• 2009

This paper presents an efficient contact detection algorithm for the plane elastostatic contact problem of the boundary element method(BEM). The data structures of the boundary element method are dissected to develop an efficient contact detection algorithm. This algorithm is consists of three parts as global searching, local searching and contact relation setting to reflect the corner node problem. Contact master and slave type elements are used in global searching step and quad-tree is selected as the spatial decomposition method in local searching step. To set up contact relation equations, global contact searching is conducted at node level and local searching is performed at element level. To verify the efficiency of the proposed contact detection algorithm of BEM, numerical example is presented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.15-20
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• 2016

Compared to the MIMO system using the spatial multiplexing methods and the MIMO system using the diversity scheme achieved a high rate, but the lower the diversity gain to improve the data transmission reliability should separate the spatial stream at the MIMO receiver. In this paper, we compared Channel capacity detection methods with the Lattice code, the 3-user interference channel and linear channel interference detection methods ZF (Zero Forcing) and MMSE (Minimum Mean Square Error) detection methods. The channel is a Diagonal channel. In other words, Diagonal channel is confirmed by the inverse matrix satisfies the properties of Jacket are element-wise inverse to $[H]_N[H]_N^{-1}=[I]_N$.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1843-1859
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• 2013

The continuous increase of the spatial resolution of remote sensing images brings great challenge to image analysis and processing. Traditional prior knowledge-based region detection and target recognition algorithms for processing high resolution remote sensing images generally employ a global searching solution, which results in prohibitive computational complexity. In this paper, a more efficient region of interest (ROI) detection algorithm based on visual attention and threshold segmentation (VA-TS) is proposed, wherein a visual attention mechanism is used to eliminate image segmentation and feature detection to the entire image. The input image is subsampled to decrease the amount of data and the discrete moment transform (DMT) feature is extracted to provide a finer description of the edges. The feature maps are combined with weights according to the amount of the "strong points" and the "salient points". A threshold segmentation strategy is employed to obtain more accurate region of interest shape information with the very low computational complexity. Experimental statistics have shown that the proposed algorithm is computational efficient and provide more visually accurate detection results. The calculation time is only about 0.7% of the traditional Itti's model.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.40-47
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• 2009

A motion adaptive video noise reduction scheme is proposed by cascading a temporal filter and a spatial filter. After a noise-robust motion detection is performed with a pre-spatial filter, the strength of the motion adaptive temporal filter is controlled by the amount of temporal movement. In order to fully utilize the temporal correlation of video signal, noisy input image is processed first by the temporal filter, therefore, image details of temporally stationary region are quite well preserved while undesired noises are suppressed. In contrast to the pre-spatial filter used for the robust motion detection, the cascaded post-spatial filter removes the remained noises by considering the strength of the temporal filter and the spatial self-similarity search results obtained from the pre-spatial filter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.93-113
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• 2020

According to information theory, non-orthogonal transmission can achieve the multiple-user channel capacity with an onion-peeling like successive interference cancellation (SIC) based detection followed by a capacity approaching channel code. However, in multiple antenna system, due to the unideal characteristic of the SIC detector, the residual interference propagated to the next detection stage will significantly degrade the detection performance of spatial data layers. To overcome this problem, we proposed a modified power-domain non-orthogonal multiple access (P-NOMA) scheme joint designed with space-time coding for multiple input multiple output (MIMO) NOMA system. First, with proper power allocation for each user, inter-user signals can be separated from each other for NOMA detection. Second, a well-designed quasi-orthogonal space-time block code (QO-STBC) was employed to facilitate the SIC-based MIMO detection of spatial data layers within each user. Last, we proposed an optimization algorithm to assign channel coding rates to balance the bit error rate (BER) performance of those spatial data layers for each user. Link-level performance simulation results demonstrate that the proposed time-space-power domain joint transmission scheme performs better than the traditional P-NOMA scheme. Furthermore, the proposed algorithm is of low complexity and easy to implement.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.6
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• pp.464-470
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• 2016

In this paper, we propose an improved face detection algorithm and determination method for drowsiness status of driver from the opening and closing frequency of the detected eye. For this purpose, face, eyes, nose, and mouth are detected based on conventional Viola-Jones face detection algorithm and spatial correlation of face. Here the spatial correlation of face is performed by DFP(Detect Face Part) based on seven characteristics. The experimental results on Caltect face image database revealed that the detection rates of noise particularly showed the improved performance of 13.78% in comparison to that of the previous Viola-Jones algorithm. Furthermore, we analyze the driver's drowsiness determination cumulative value of the eye closed state as a function of time based on SVM (Support Vector Machine) and PERCLOS(Percentage Closure of Eyes). The experimental results confirmed the usefulness of the proposed method by obtaining a driver's drowsiness determination rate of 93.28%.