• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.1
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• pp.49-62
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• 2020

This study was conducted as a basic study to develop the HSI(Habitat Suitability Index) model of Pelophylax chosenicus based on the research on the ecological and habitat status of Pelophylax chosenicus and the literature research on the HSI model. The habitat variables of Pelophylax chosenicus are the altitude of the spawning pond, the habitat area, the distance from wetland, the soil(aptitude grade for paddy field), the place for eating such as paddy field and wetlands(land cover) and the distance from Predator(Lithobates catesbeianus) distribution area. Based on the existing literature of Pelophylax chosenicus, the results of field surveys and expert opinions, the SI(Suitability Index) model and HSI model were developed and applied to the site to examine the applicability of the HSI model. As a result of application, SI 4 and SI 5 with varying SI values seem to have a major influence on the HSI. In addition, it is considered that the HSI model is an arithmetic mean of SI models, which has a major impact on HSI. The HSI model can be an important basis for the habitat evaluation and restoration model of Pelophylax chosenicus. In particular, it is highly applicable to the selection and evaluation of alternative habitats for Pelophylax chosenicus.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.4
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• pp.429-435
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• 2009

This paper propose color assessment method using HSI model to evaluate quantitative quality of mosaic images by aerial digital frame camera. Firstly, we convert RGB color into HSI model and we extract six pixel information of S and I corresponding to H from adjacency image by using HSI model. Secondly, a method to measure similarity and contrast is proposed and performed for assesment of observation regarding adjacency images. Through these procedure, we could generate four parameters. We could observe that both of the evaluation results by proposed method and the evaluation results by visual were almost similar. This facts support that our method based on several formula can be an objective method to evaluate a quality of mosaic images itself.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.151-159
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• 2013

The building information should be up-to-date information and propagated rapidly for urban modeling, terrain analysis, life information, navigational system, and location-based services(LBS), hence the most recent and updated data of the building information have been required of researchers. This paper presents the developed system to extract the 3-dimension spatial information from aerial orthoimage and LiDAR data of HSI color model. In particular, this paper presents the image processing algorithm to extract the outline of specific buildings and generate the building polygon from the image using HIS color model, recursive backtracking algorithm and the search maze algorithm. Also, this paper shows the effectivity of the HIS color model in the image segmentation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.1004-1012
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• 2007

In this paper, we proposed a new car license plate recognition method using an unsupervised ART2 algorithm with HSI color model. The proposed method consists of two main modules; extracting plate area from a vehicle image and recognizing the characters in the plate after that. To extract plate area, hue(H) component of HSI color model is used, and the sub-area containing characters is acquired using modified fuzzy binarization method. Each character is further divided by a 4-directional edge tracking algorithm. To recognize the separated characters, noise-robust ART2 algorithm is employed. When the proposed algorithm is applied to recognize license plate characters, the extraction rate is better than that of existing RGB model and the overall recognition rate is about 97.4%.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.5
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• pp.455-463
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• 2008

The shadows, which is generated when acquiring data using optical sensor, mutilates consistency of brightness for same objects in the images. Hence, it makes a trouble to interpret the ground information. This study is focused on detecting the shadowing area in the images. And only single image is used without any other data which is acquired from different source. Also, This study presents the method using HSI color model, especially, using I(intensity) information, and the intensity clustering algorithm. Then, we illuminate the effects of shadow by FFT(Fast Fourier Transform).

• Communications for Statistical Applications and Methods
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• v.23 no.3
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• pp.203-213
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• 2016

We investigate volatility spillover aspects of realized volatilities (RVs) for the log returns of the Korea Composite Stock Price Index (KOSPI) and the Hang Seng Index (HSI) from 2009-2013. For all RVs, significant long memories and asymmetries are identified. For a model selection, we consider three commonly used time series models as well as three models that incorporate long memory and asymmetry. Taking into account of goodness-of-fit and forecasting ability, Leverage heteroskedastic autoregressive realized volatility (LHAR) model is selected for the given data. The LHAR model finds significant decompositions of the spillover effect from the HSI to the KOSPI into moderate negative daily spillover, positive weekly spillover and positive monthly spillover, and from the KOSPI to the HSI into substantial negative weekly spillover and positive monthly spillover. An interesting result from the analysis is that the daily volatility spillover from the HSI to the KOSPI is significant versus the insignificant daily volatility spillover of the KOSPI to HSI. The daily volatility in Hong Kong affects next day volatility in Korea but the daily volatility in Korea does not affect next day volatility in Hong Kong.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.92-98
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• 2022

This paper proposes a new method of the traffic signal detection and the recognition in an HSI color model. The proposed method firstly converts a ROI image in the RGB model to in the HSI model to segment the color of a traffic signal. Secondly, the segmented colors are dilated by the morphological processing to connect the traffic signal light and the signal light case and finally, it extracts the traffic signal light and the case by the aspect ratio using the connected component analysis. The extracted components show the detection and the recognition of the traffic signal lights. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. The system was fixedly installed in a moving vehicle, and it recorded a video like a vehicle black box. Each frame of the recorded video was extracted, and then the proposed method was tested. The results show that the proposed method is successful for the detection and the recognition of traffic signals.

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.142-148
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• 2011

The final aim of the present study is to develop the intelligent robot, emulating human synesthetic skills which make it possible to associate a color image with a specific sound. This can be done on the basis of the mutual conversion between color image and sound. As a first step of the final goal, this study focused on a basic system using a conversion of color image into sound. This study describes a proposed method to convert color image into sound, based on the likelihood in the physical frequency information between light and sound. The method of converting color image into sound was implemented by using HSI histograms through RGB-to-HSI color model conversion, which was done by Microsoft Visual C++ (ver. 6.0). Two different color images were used on the simulation experiments, and the results revealed that the hue, saturation and intensity elements of each input color image were converted into fundamental frequency, harmonic and octave elements of a sound, respectively. Through the proposed system, the converted sound elements were then synthesized to automatically generate a sound source with wav file format, using Csound.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.222-224
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• 2009

This paper presents an algorithm that extracts road lane's specific information by using HSI color information and performance enhancement of lane detection base on vision processing of drive assist. As a preprocessing for high speed lane detection, the optimal extraction of region of interest for lane boundary(ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled and it also increases reliabilities by deleting edges those are misrecognized. Road lane is extracted with simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since noise can be removed by using saturation and brightness of HSI color model. Also it searches for the road lane's color information and extracts characteristics. The real road experimental results are presented to evaluate the effectiveness of the proposed method.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.4
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• pp.1-11
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• 2020

This study aimed to develop the HSI (Habitat Suitability Index) model of Cypripedium guttatum. and to verify this model by applying to the candidate sites for replacement habitat. The development of HSI and SI (Suitability Index) model was conducted based on the existing literature, field surveys, and expert opinions for information on ecological habitat characteristics. Seven variables were selected as habitat variables including mean maximum temperature in Jul.-Aug., lighting, slope, altitude, effective soil depth, soil texture, and artificial overexploitation (i.e. protected areas). HSI model was developed for C. guttaum based on these variables. This HSI model showed high applicability to selection and evaluation of replacement habitats for C. guttaum. Our findings could provide the basic information on habitat assessment to prevent the extinction of endangered C. guttatum. However, since there is a limitation that the survey data were insufficient, further field surveys should be conducted on several habitat types to improve the accuracy of the HSI model.