• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.281-286
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• 2006

In this study, acquired time series Landsat TM/ETM+ image to extract land surface temperature for wide-area region and executed geometric correction and radiometric correction. And extracted land surface temperature using NASA Model, and I achieved the first correction by perform land coverage category for study region and applies characteristic emission rate. Land surface temperature that acquire by the first correction analyzed correlation with Meteorological Administration's temperature data by regression analysis, and established correction formula. And I wished to improve accuracy of land surface temperature extraction using satellite image by second correcting deviations between two datas using establishing correction formula. As a result, land surface temperature that acquire by 1,2th correction could correct in mean deviation of about ${\pm}3.0^{\circ}C$ with Meteorological Administration data. Also, could acquire land surface temperature about study region by relative high accuracy by applying to other Landsat image for re-verification of study result.

• Journal of the Korea Computer Industry Society
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• v.3 no.12
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• pp.1669-1678
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• 2002

Symmetry region searching can extract face region without a prior information in an image by using symmetric. However, this method requires a plenty of the computation time because the mask size to process symmetry region searching must be larger than the size of object such as eye, nose and mouth in face. In this paper, we proposed symmetric by using symmetry region searching in the reduced image to reduce computation time of symmetry region searching. It was applied to this method in an original image. To extract exact face region, we also experimented face region searching by using domain division in extraction legion.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.960-968
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• 2018

The mobile visual search service uses a query image to acquire linkage information through pre-constructed DB search. From the standpoint of this purpose, it would be more useful if you could perform a search on a web-based keyword search system instead of a pre-built DB search. In this paper, we propose a representative query extraction algorithm to be used as a keyword on a web-based search system. To do this, we use image classification labels generated by the CNN (Convolutional Neural Network) algorithm based on Deep Learning, which has a remarkable performance in image recognition. In the query extraction algorithm, dictionary meaningful words are extracted using Wikipedia, and hierarchical categories are constructed using WordNet. The performance of the proposed algorithm is evaluated by measuring the system response time.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1211-1212
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• 2008

In this paper, we propose image process modeling as a part of location based surveillance system for unauthorized target recognition and tracking in harbor, airport, military zone. For this, we compress and store background image in lower resolution and perform object extraction and motion tracking by using sobel edge detection and difference picture method between real images and a background image. In addition to, we use Independent Component Analysis Neural Network for moving target recognition. Experiments are performed for object extraction and tracking of moving targets on road by using static camera in 20m height building and it shows the robust results.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.789-790
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• 2008

In this paper, we introduce the multi-target-based auto surveillance algorithm. Multi-target-based surveillance system detects intrusion objects in the specified areas. The proposed algorithm can divide into two parts: i) background generation, ii) object extraction. In this paper, one of the optical flow equation methods for estimation of gradient method used to generate the background [2]. In addition, the objects and back- ground video images that are continually entering the differential extraction.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.425-428
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• 2003

Recently, the IDS(Intrusion Detection System) using a video camera is an important part of the home security systems which start gaining popularity. However, the video intruder detection has not been widely used in the home surveillance systems due to its unreliable performance in the environment with abrupt illumination change. In this paper, we propose an effective moving edge extraction algorithm from a sequence image. The proposed algorithm extracts edge segments from current image and eliminates the background edge segments by matching them with reference edge list, which is updated at every frame, to find the moving edge segments. The test results show that it can detect the contour of moving object in the noisy environment with abrupt illumination change.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1113-1116
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• 1999

In this papers, we proposes a efficient compression method of an image using the extraction of boundary region of DCT in MPEG-1. DCT coefficients have from low frequency to high frequency various components. After performing DCT to an image, the data is compressed to contain the boundary Region by quantization, and the information of boundary Region can be extracted by inverse DCT. In those, I chose frequency components susceptible to the boundary through the many experiences. In this paper, boundary can be selected by dividing low frequency by big quantization coefficient and dividing high frequency by small quantization coefficient without degrading visual qualify in MPEG-1. Also it is predicted that to reduce high frequency value will be good in noisy environments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.247-250
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• 2003

This paper describes the extraction method for brain region using cellular automata from the brain MR image. In the first removing the background from the brain MR image, and then extracting the brain region by applying the cellular automata rule obtained from histogram analysis information. The results on some experimental results showed that the PSNR is 42.11(dB) on image quality and also the correlation factor is estimated 98.46%. The result of this study can be used as the auto-diagnostics system.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.119-128
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• 1994

In this paper, we propose a method for facial feature extraction and recognition algorithm using neural networks. First we extract a face part from the background image based on the knowledge that it is located in the center of an input image and that the background is homogeneous. Then using vertical and horizontal projections. We extract features from the separated face image using knowledge base of human faces. In the recognition step we use the back propagation algorithm of the neural networks and in the learning step to reduce the computation time we vary learning and momentum rates. Our technique recognizes 6 women and 14 men correctly.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.1
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• pp.74-84
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• 1988

This paper presents feature extraction technique for linear image using edge detection algorithms. The process of edge finding consists of determining edge magnitud and direction by convolution of an image with a number of edge masks, of thinning and ghresholding these edge magnitudes, of linking the edge elemtnts based on proximity ans orientation, and finally, of approximating the linked elements by piede-wise linear segmentss. These techniques are intened to be general and opplications to terminal detection and road recognition tasks are described. The presentation will be helpful to other researchers attempting to implement similar algorithms.