• Journal of KIISE:Software and Applications
• /
• v.27 no.1
• /
• pp.74-83
• /
• 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
• /
• v.5 no.6
• /
• pp.79-91
• /
• 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
• /
• v.22 no.11
• /
• pp.1455-1461
• /
• 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
• /
• v.19 no.4
• /
• pp.93-98
• /
• 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
• /
• v.17 no.9
• /
• pp.99-112
• /
• 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
• /
• v.22 no.12
• /
• pp.51-57
• /
• 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
• /
• v.14 no.12
• /
• pp.63-73
• /
• 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
• /
• v.36 no.5_1
• /
• pp.847-860
• /
• 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.

• The Journal of Korean Society for Radiation Therapy
• /
• v.22 no.2
• /
• pp.75-83
• /
• 2010

Purpose: It aims to evaluate the location change and tendency of hepatic and intrahepatic tumors according to gastric volume and change of location. Materials and Methods: It studied 9 patients with hepatic tumors who visited Gangnam Severance Hospital from March 2009 to April 2010 and who underwent CT or PET (Positron Emission Tomography) within 2 weeks before CT-simulation. The patients fasted for 6 hours before CT-simulation and drank 240~250 cc of water just before CT or PET for image fusion. Those two types of images were fused to RTP (Radiation Treatment Planning, Pinnacle 8.0h) focusing on bone structure of individual patients. Results: They drank 240~260 cc of water but their stomach volume after drinking water varied from 259.3 cc to 495.4 cc. Even though individual differences existed in the change of stomach volume before and after drinking water, the volume was increased by 130 cc (174%) on average. The change in absolute distance between the centers of tumors ranged from 0.52 cm to 3.04 cm (1.52 cm on average); from 0.1 cm to 1.35 cm (0.44 cm on average) in cranial-caudal direction; from 0.05 cm to 2.75 cm (1.22 cm on average) in left-right direction; and from 0.05 cm to 1.85 cm (0.33 cm on average) in ventral-dorsal direction. Conclusion: It is hard to predict the movement of tumors by observing stomach movement, due to great individual differences; however, it was observed that the location of hepatic tumors was right-sided as the stomach was filled with water. Thus, it is recommended to maintain the fastened state to secure the accuracy of hepatic tumor treatment. If it cannot maintain the fastened state, it is recommended to measure stomach volumes and movement in the patient to consider the movement of hepatic tumors before radiation treatment.

• Economic and Environmental Geology
• /
• v.47 no.1
• /
• pp.39-48
• /
• 2014

In coastal region, estuaries have complex environments where dissolved and particulate matters are mixed with marine water and substances. Suspended sediment (SS) dynamics in coastal water, in particular, plays a major role in erosion/deposition processes, biomass primary production and the transport of nutrients, micropollutants, heavy metals, etc. Temporal variation in suspended sediment concentration (SSC) can be used to explain erosion/sedimentation patterns within coastal zones. Remotely sensed data can be an efficient tool for mapping SS in coastal waters. In this study, we analyzed the variation in SSC in coastal water using the Geostationary Ocean Color Imager (GOCI) and Landsat Enhanced Thematic Mapper Plus (ETM+) in Gyeonggi-bay. Daily variations in GOCI-derived SSC showed low values during ebb time. Current velocity and water level at 9 and 10 am is 37.6, 28.65 $cm{\cdot}s^{-1}$ and -1.23, -0.61 m respectively. Water level has increased to 1.18 m at flood time. In other words, strong current velocity and increased water level affected high SSC value before flood time but SSC decreased after flood time. Also, we compared seasonal SSC with the river discharge from the Han River and the Imjin River. In summer season, river discharge showed high amount, when SSC had high value near the inland. At this time SSC in open sea had low value. In contrast, river discharge amount from inland showed low value in winter season and, consequently, SSC in the open sea had high value because of northwest monsoon.