• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.33-45
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• 2011

In this paper, we present a method for extracting video objects efficiently by using the modified graph cut algorithm based on contour information. First, we extract objects at the first frame by an automatic object extraction algorithm or the user interaction. To estimate the objects' contours at the current frame, motion information of objects' contour in the previous frame is analyzed. Block-based histogram back-projection is conducted along the estimated contour point. Each color model of objects and background can be generated from back-projection images. The probabilities of links between neighboring pixels are decided by the logarithmic based distance transform map obtained from the estimated contour image. Energy of the graph is defined by predefined color models and logarithmic distance transform map. Finally, the object is extracted by minimizing the energy. Experimental results of various test images show that our algorithm works more accurately than other methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.107-115
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• 2002

In this paper, we describe a novel method to generate an intermediate scene using BDM (Bidirectional Disparity Morphing) from the parallel stereopair. Because an image is composed of several layers and each layer has a similar disparity, it is available to use the block based disparity estimation. In order to prevent the false correspondence, however, we closely investigate the corresponding block as we adaptively vary the block size according to the estimation error. Therefore, we can detect the occlusion because of larger estimation error of the occluded region. We define three occluding patterns, which ate derived from the peculiar property of the disparity map, in order to smooth the computed disparity map. The filtered disparity map using these patterns presents that the false disparities ate well corrected and the boundary between foreground and background becomes sharper. As a result, we can improve the quality of the intermediate scenes.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.10
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• pp.1443-1449
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• 2013

Automatic detection of vehicles in front is an integral component of many advanced driver-assistance system, such as collision mitigation, automatic cruise control, and automatic head-lamp dimming. Regardless day and night, tail-lights play an important role in vehicle detecting and status recognizing of driving in front. However, some drivers do not know the status of the tail-lights of vehicles. Thus, it is required for drivers to inform status of tail-lights automatically. In this paper, a recognition method of status of tail-lights based on video processing and recognition technology is proposed. Background estimation, optical flow and Euclidean distance is used to detect vehicles entering tollgate. Then saliency map is used to detect tail-lights and recognize their status in the Lab color coordinates. As results of experiments of using tollgate videos, it is shown that the proposed method can be used to inform status of tail-lights.

• Journal of Animal Science and Technology
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• v.56 no.7
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• pp.23.1-23.7
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• 2014

Background: Scanning of the genome for selection signatures between breeds may play important role in understanding the underlie causes for observable phenotypic variations. The discovery of high density single nucleotide polymorphisms (SNPs) provide a useful starting point to perform genome-wide scan in pig populations in order to identify loci/candidate genes underlie phenotypic variation in pig breeds and facilitate genetic improvement programs. However, prior to this study genomic region under selection in commercially selected Berkshire and Korean native pig breeds has never been detected using high density SNP markers. To this end, we have genotyped 45 animals using Porcine SNP60 chip to detect selection signatures in the genome of the two breeds by using the $F_{ST}$ approach. Results: In the comparison of Berkshire and KNP breeds using the FDIST approach, a total of 1108 outlier loci (3.48%) were significantly different from zero at 99% confidence level with 870 of the outlier SNPs displaying high level of genetic differentiation ($F_{ST}{\geq}0.490$). The identified candidate genes were involved in a wide array of biological processes and molecular functions. Results revealed that 19 candidate genes were enriched in phosphate metabolism (GO: 0006796; ADCK1, ACYP1, CAMK2D, CDK13, CDK13, ERN1, GALK2, INPP1; MAK, MAP2K5, MAP3K1, MAPK14, P14KB, PIK3C3, PRKC1, PTPRK, RNASEL, THBS1, BRAF, VRK1). We have identified a set of candidate genes under selection and have known to be involved in growth, size and pork quality (CART, AGL, CF7L2, MAP2K5, DLK1, GLI3, CA3 and MC3R), ear morphology and size (HMGA2 and SOX5) stress response (ATF2, MSRB3, TMTC3 and SCAF8) and immune response (HCST and RYR1). Conclusions: Some of the genes may be used to facilitate genetic improvement programs. Our results also provide insights for better understanding of the process and influence of breed development on the pattern of genetic variations.

• Journal of Ecology and Environment
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• v.45 no.4
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• pp.255-263
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• 2021

Background: Ecosystem service mapping is an important tool for decision-making in landscape planning and natural resource management. Today, pollination service mapping is based on the Lonsdorf model (InVEST software) that determines the availability of nesting and floral resources for each land cover and estimates pollination according to the foraging range of the desired species. However, it is argued that the Lonsdorf model has significant limitations in estimating pollination in a landscape that can affect the results of this model. Results: This paper presents a free software, named PollMap, that does not have the limitations of the Lonsdorf model. PollMap estimates the pollination service according to a modified version of the Lonsdorf model and assumes that only cells within the flight range of bees are important in the pollination mapping. This software is produced for estimating and mapping crop pollination in agricultural landscapes. The main assumption of this software is that in the agricultural landscapes, which are dominated by forest and agriculture ecosystems, forest patches serve only as a nesting habitat for wild bees and the surrounding fields provide floral resources. Conclusion: The present study provided new software for mapping crop pollination in agricultural landscapes that does not have the limitations of the Lonsdorf model. We showed that the use of the Lonsdorf model for pollination mapping requires attention to the limitations of this model, and by removing these limitations, we will need new software to obtain a reliable mapping of pollination in agricultural landscapes.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.519-526
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• 2022

Basically, autonomous vehicles drive using road and traffic information collected by various sensors. However, it is known that there is a limitation to realizing fully autonomous driving with only such technologies and information. In recent, various efforts are being made to overcome the limitations of sensor-based autonomous driving, and efforts are also underway to utilize more specific and accurate road and traffic information, called local dynamic map (LDM). However, LDM-related data standards and specifications have not yet been sufficiently verified, and research on the spatiotemporal scope of LDM during autonomous driving is extremely limited. Based on this background, the purpose of this study is to identify these limitations through an analysis of previous LDM-related studies and to present a framework for calculating the spatiotemporal activation section of LDM-based road and traffic information.

• Journal of People, Plants, and Environment
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• v.24 no.5
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• pp.519-527
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• 2021

Background and objective: This study was conducted to establish a Plant Hardiness Zone (PHZ) map, investigate the effect of global warming on changes in PHZ, and elucidate the difference in the distribution of evergreen trees between the central and southern region within hardiness Zone 7b in Korea. Methods: Mean annual extreme minimum temperature (EMT) and related temperature fluctuation data for 40 years (1981 to 2020) in each of the meteorological observation points were extracted from the Open MET Data Portal of the Korea Meteorological Administration. Using EMT data from 60 meteorological observation points, PHZs were classified according to temperature range in the USDA Plant Hardiness Zone Map. Changes in PHZs for each decade related to the effects of global warming were analyzed. Temperature fluctuation before and after the day of EMT were analyzed for 4 areas of Seoul, Suwon, Suncheon, and Jinju falling under Zone 7b. For statistical analysis, descriptive statistics and ANOVA were performed using the IBM SPSS 22 Statistics software package. Results: Plant hardiness zones in Korea ranged from 6a to 9b. Over four decades, changes to warmer PHZ occurred in 10 areas, especially in colder ones. Based on the analysis of daily temperature fluctuation, the duration of sub-zero temperatures was at least 2 days in Seoul and Suwon, while daily maximum temperatures were above zero in Suncheon and Jinju before and after EMT day. Conclusion: It was found that the duration of sub-zero temperatures in a given area is an important factor affecting the distribution of evergreen trees in PHZ 7b.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.67-73
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• 2007

This paper presents a panoramic reference image generation based automatic algorithm for moving objects detection robust to illumination variations under moving camera. Background image is generated by rotating the fixed the camera on the tripod horizontally. aligning and reorganizing this images. In generation of the cylindrical panoramic image, most of previous works assume the static environment. We propose the method to generating the panoramic reference image from dynamic environments in this paper. We develop an efficient approach for panoramic reference image generation by using accumulated edge map as well as method of edge matching between input image and background image. We applied the proposed algorithm to real image sequences. The experimental results show that panoramic reference image generation robust to illumination variations can be possible using the proposed method.

• Transactions on Electrical and Electronic Materials
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• v.13 no.1
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• pp.10-15
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• 2012

In conventional, skin detection methods using for skin color definitions is based on prior knowledge. By experimentation, the threshold value for dividing the background from the skin region is determined subjectively. A drawback of such techniques is that their performance is dependent on a threshold value which is estimated from repeated experiments. To overcome this, the present paper introduces a skin region detection method. This method uses a histogram approximation based on the mean shift algorithm. This proposed method applies the mean shift procedure to a histogram of a skin map of the input image. It is generated by comparing with the standard skin colors in the $C_bC_r$ color space. It divides the background from the skin region by selecting the maximum value according to the brightness level. As the histogram has the form of a discontinuous function. It is accumulated according to the brightness values of the pixels. It is then, approximated by a Gaussian mixture model (GMM) using the Bezier curve technique. Thus, the proposed method detects the skin region using the mean shift procedure to determine a maximum value. Rather than using a manually selected threshold value, as in existing techniques this becomes the dividing point. Experiments confirm that the new procedure effectively detects the skin region.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.38-47
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• 2013

An image coding based on MRC model, a kind of multi-layer image model, first segments a screen image into foreground, mask, and background layers, and then compresses each layer using a codec that is suitable to the layer. The mask layer defines the position of foreground regions such as textual and graphical contents. The colour signal of the foreground (background) region is saved in the foreground (background) layer. The mask layer which contains the segmentation result of foreground and background regions is of importance since its accuracy directly affects the overall coding performance of the codec. This paper proposes a new layer segmentation algorithm for the MRC based image coding. The proposed method extracts text pixels from the background using morphological top hat filtering. The application of white or black top hat transformation to local blocks is controlled by the information of relative brightness of text compared to the background. In the proposed method, the boundary information of text that is extracted from the edge map of the block is used for the robust decision on the relative brightness of text. Simulation results show that the proposed method is superior to the conventional methods.