• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.3
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• pp.206-211
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• 2020

It is Face recognition is a very important process in image monitoring and it is a form of biometric technology. The recognition process involves many variables and is highly complex, so the software development has only begun recently with the development of hardware. Face detection technology using the CCTV is a process that precedes face analysis, and it is a technique that detects where the face is in the image. Research in face detection and recognition has been difficult because the human face reacts sensitively to different environmental conditions, such as lighting, color of skin, direction, angle and facial expression. The utility and importance of face recognition technology is coming into the limelight over time, but many aspects are being overlooked in the facial area detection technology that must precede face recognition. The system in this paper can detect tilted faces that cannot be detected by the AdaBoost detector and It could also be used to detect other objects.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2003.11a
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• pp.61-64
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• 2003

무손실 이미지 압축은 (Lossless Image Compression)은 손실이미지 압축(Lossy Image Compression)에 비해, 압축률(compression ratio)은 떨어지지만, 반면 원이미지와 복원이미지가 완전히 일치하므로, 원인이미지의 품질을 그대로 유지학 수 있다. 따라서, 이미지의 품질(Quality)과 압축효율(compression ratio)은 서로 상반된 관계에 있으며, 지금도 좀 더 놀은 압축효과를 얻으려는 여러 무손실 압축 방법이 발표되고 있다. 무손실 이미지 압축은 이미지의 정확성과 정밀성이 요구되는, 의료영양분야에서 가장 널리 쓰이고 있으며, 그밖에, 원본이미지를 기본으로 다른 이미지프로세싱이 필요한 경우, 압축 복원을 반복적으로 수행할 필요가 있을 때, 기타 사진 예술분야, 원격 영상 등 정밀성이 요구되는 분양에서 쓰이고 있다. [7]. 무손실 이미지 압축의 가장 대표적인 CALIC[3]과 JPEG_LS[2]를 들 수 있다. CALIC은 비교적 높은 압축률을 나타내지만, 3-PASS의 과정을 거치는 복잡도가 지적되고 있다. 반면 JPEG-LS는 압축률은 CALIC에 미치지 못하지만 빠른 코딩/디코딩 속도를 보인다. 본 논문에서는 여거 가지의 예측 모드를 두어, 블록단위별로 주변 CONTEXT에 따라, 최상의 예측 모드를 판단하여, 이를 적용, 픽셀의 여러 값을 최소화하였다. 그 후 적응산술 부호기(Adaptive arithmetc coder)를 이용하여, 인코딩을 하였다. 이때 최대 에러값은 64를 넘지 않게 했으며, 또한 8*8블록별로 에러의 최대값을 측정하여 그 값을 $0\~7$까지의 8개의 대표값으로 양자화하는 방법을 통하여 그에 따라 8개의 보호화 심볼 모델중 알맞은 모델에 적용하였다. 이를 통해, 그 소화값의 확률 구간을 대폭 넓힘으로써, 에러 이미지가 가지고 있는 엔트로피에 좀 근접하게 코딩을 할 수 있게 되었다. 이 방법은 실제로 Arithmetic Coder를 이용하는 다른 압축 방법에 그리고 적용할 수 있다. 실험 결과 압축효율은 JPEG-LS보다 약 $5\%$의 압축 성능 개선이 있었으며, CALIC과는 대등한 압축률을 보이며, 부호화/복호화 속도는 CALIC보다 우수한 것으로 나타났다.

• Journal of KIISE:Software and Applications
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• v.27 no.1
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• pp.74-83
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• 2000

There is a rapid increase in the use of digital video information in recent years. Especially, user requires the environment which retrieves video from passive access to active access, to be more efficiently. we need to implement video retrieval system including video parsing, clustering, and browsing to satisfy user's requirement. In this paper, we first divide video sequence to shots which are primary unit for automatic indexing, using a hybrid method with mixing histogram method and pixel-based method. After the shot boundaries are detected, corresponding key frames can be extracted. Key frames are very important portion because they help to understand overall contents of video. In this paper, we first analyze camera operation in video and then select different number of key frames depend on shot complexity. At last, we compose panorama images from shots which are containing panning or tilting in order to provide more useful and understandable browsing environment to users.

• Journal of Internet Computing and Services
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• v.5 no.6
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• pp.79-91
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• 2004

Various facial pose detection and recognition has been a difficult problem. The problem is due to the fact that the distribution of various poses in a feature space is mere dispersed and more complicated than that of frontal faces, This thesis proposes a robust pose-expression-invariant face recognition method in order to overcome insufficiency of the existing face recognition system. First, we apply the TSL color model for detecting facial region and estimate the direction of face using facial features. The estimated pose vector is decomposed into X-V-Z axes, Second, the input face is mapped by deformable template using this vectors and 3D CANDIDE face model. Final. the mapped face is transformed to frontal face which appropriates for face recognition by the estimated pose vector. Through the experiments, we come to validate the application of face detection model and the method for estimating facial poses, Moreover, the tests show that recognition rate is greatly boosted through the normalization of the poses and expressions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1455-1461
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• 2018

This paper presents a kernel analysis of weighted linear interpolation based on even-odd decomposition (EOD). The EOD method has advantages in that it provides low-complexity and improved image quality than the CCI method. However, since the kernel of EOD has not studied before and its analysis has not been addressed yet, this paper proposes the kernel function and its analysis. The kernel function is divided into odd and even terms. And then, the kernel is accomplished by summing the two terms. The proposed kernel is adjustable by a parameter. The parameter influences efficiency in the EOD based WLI process. Also, the kernel shapes are proposed by adjusting the parameter. In addition, the discussion with respect to the parameter is given to understand the parameter. A preliminary experiment on the kernel shape is presented to understand the adjustable parameter and corresponding kernel.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.93-98
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• 2019

On today, optical system are the next generation weapon systems being studied in many countries, starting from USA. One of the most important technologies in optical system is a high-speed automatic target tracking system that can continuously track high-speed moving small targets. This paper designs an automatic target tracking system based on a correlated trekker that is robust against rapid shape changes for fast moving targets and small targets at a distance. The proposed system showed about 98% success rate in response to the targets that are under a complex background such as drone, ranger, etc.

• The Journal of Korean Institute of Information Technology
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• v.17 no.9
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• pp.99-112
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• 2019

Cracks on pavement surfaces are critical signs and symptoms of the degradation of pavement structures. Image-based pavement crack detection is a challenging problem due to the intensity inhomogeneity, topology complexity, low contrast, and noisy texture background. In this paper, we address the problem of pavement crack detection and segmentation at pixel-level based on a Deep Neural Network (DNN) using gray-scale images. We propose a novel DNN architecture which contains a modified U-net network and a high-level features network. An important contribution of this work is the combination of these networks afforded through the fusion layer. To the best of our knowledge, this is the first paper introducing this combination for pavement crack segmentation and detection problem. The system performance of crack detection and segmentation is enhanced dramatically by using our novel architecture. We thoroughly implement and evaluate our proposed system on two open data sets: the Crack Forest Dataset (CFD) and the AigleRN dataset. Experimental results demonstrate that our system outperforms eight state-of-the-art methods on the same data sets.

• Journal of the Korean GEO-environmental Society
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• v.22 no.12
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• pp.51-57
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• 2021

Underground lifelines such as water supply/sewer pipe, power cable and gas pipe are indispensable facilities to the life of urban society. These lifelines have been constructed long time ago and buried positioning information is not precisely recorded. Moreover, they have been concentrated on the narrow area and are complicatedly entangled in 3-dimension. In the fourth industrial revolution, a 3-dimensional visualization for underground lifelines is strongly required, and a database (D/B) with precise positioning information should be preceded. In this study, image processing technology for precise positioning of underground buried lifelines is introduced, which is able to build the database more accurately, efficiently and practically.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.63-73
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• 2009

This paper presents a vehicle detection method that uses convolution matching method based on a simple color information. An input image is expressed as 8 oriented color expression(Red, Green, Blue, White, Black, Cyan, Yellow, Magenta) considering an orientation of a pixel color vector. It makes the image very reliable and strong against changes of illumination condition or environment. This paper divides the vehicle detection into a hypothesis generation step and a hypothesis verification step. In the hypothesis generation step, the vehicle candidate region is found by vertical edge and shadow. In the hypothesis verification step, the convolution matching and the complexity of image edge are used to detect real vehicles. It is proved that the proposed method has the fast and high detection rate on various experiments where the illumination source and environment are changed.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.847-860
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• 2020

The 2-pass DInSAR (Differential Interferometric SAR) processing steps for DEM generation consist of the co-registration of SAR image pair, interferogram generation, phase unwrapping, calculation of DEM errors, and geocoding, etc. It requires complicated steps, and the accuracy of data processing at each step affects the performance of the finally generated DEM. In this study, we developed an improved method for enhancing the performance of the DEM generation method based on the 2-pass DInSAR technique of TanDEM-X bistatic SAR images was developed. The developed DEM generation method is a method that can significantly reduce both the DEM error in the unwrapped phase image and that may occur during geocoding step. The performance analysis of the developed algorithm was performed by comparing the vertical accuracy (Root Mean Square Error, RMSE) between the existing method and the newly proposed method using the ground control point (GCP) generated from GPS survey. The vertical accuracy of the DInSAR-based DEM generated without correction for the unwrapped phase error and geocoding error is 39.617 m. However, the vertical accuracy of the DEM generated through the proposed method is 2.346 m. It was confirmed that the DEM accuracy was improved through the proposed correction method. Through the proposed 2-pass DInSAR-based DEM generation method, the SRTM DEM error observed by DInSAR was compensated for the SRTM 30 m DEM (vertical accuracy 5.567 m) used as a reference. Through this, it was possible to finally create a DEM with improved spatial resolution of about 5 times and vertical accuracy of about 2.4 times. In addition, the spatial resolution of the DEM generated through the proposed method was matched with the SRTM 30 m DEM and the TanDEM-X 90m DEM, and the vertical accuracy was compared. As a result, it was confirmed that the vertical accuracy was improved by about 1.7 and 1.6 times, respectively, and more accurate DEM generation was possible with the proposed method. If the method derived in this study is used to continuously update the DEM for regions with frequent morphological changes, it will be possible to update the DEM effectively in a short time at low cost.