• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.825-828
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• 2006

The most commonly used techniques for image magnification are interpolation based. However, the magnified images produced by this technique often appear blocking and blurring phenomenon when the image is enlarged. In this paper, we enhanced image magnification algorithm using edge information. The proposed algorithm not used interpolation based but by using sub-band of input image in extrapolation. According to mapping relationship in pyramid, we calculated up-band information to magnify. In experiments, the proposed model shows solved the problem of image loss like the blocking and blurring phenomenon. As the result, it is faster and higher resolution than traditional magnification algorithms.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.813-816
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• 2018

X-ray 진단에서 그리드 하드웨어의 사용은 산란선에 의한 영상의 왜곡을 보정할 수 있는 장점이 있는 반면, 반복되는 라인 형태의 그리드 아티팩트를 발생시키는 부작용을 수반한다. 본 논문에서는 이러한 그리드 라인을 제거하는 방법론으로서 이산코사인변환(DCT: discrete cosine transform)을 사용 하는 기법을 제안한다. X-ray 영상에서 그리드 라인의 특성은 피사체의 형태와 영상의 영역에 따라 서로 다른 특성을 갖는다. 이에 본 연구에서는 동적으로 재구성되는 분할 구조를 기반으로 DCT 변환을 적용하고 개별 영역별로 필터전달함수를 최적화하는 방법을 채택하였다. 추출된 주파수 영역 데이터에 대하여 그리드 라인의 대역을 검출하는 알고리즘을 제안하였으며, 필터전달함수로 Kaiser윈도우와 Butterworth 필터를 조합한 형태의 밴드스톱필러(BSF: band stop filter)를 구현하였다. 또한 블로킹 현상을 개선하기 위하여 다중 영상으로부터 경계선 부분의 픽셀값을 결정하는 방법론을 제안하였다. 제안된 이론에 대하여 실제 영상을 사용한 실험결과로부터 그 타당성을 평가하였다.

• Journal of IKEEE
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• v.24 no.1
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• pp.97-105
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• 2020

A thermal imaging sensor receives the radiating energy from the target and the background, so it has been widely used for detection, tracking, and classification of targets at night for military purpose. In recognizing the target automatically using thermal images, if the correct edges of object are used then it can generate the classification results with high accuracy. However since the thermal images have lower spatial resolution and more blurred edges than color images, the accuracy of the classification using thermal images can be decreased. In this paper, to overcome this problem, a new hierarchical classifier using both shape and local features based on the segmentation reliabilities, and the class/pose updating method for vehicle classification are proposed. The proposed classification method was validated using thermal video sequences of more than 20,000 images which include four types of military vehicles - main battle tank, armored personnel carrier, military truck, and estate car. The experiment results showed that the proposed method outperformed the state-of-the-arts methods in classification accuracy.

• Journal of Broadcast Engineering
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• v.16 no.4
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• pp.669-679
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• 2011

In this paper, we propose a POCS based irregularly sampled image interpolation method exploiting non-local block-based wavelet shrinkage denoising algorithm. The method provides convex sets to improve the performance. The Delaunay triangulation interpolation is first applied to interpolate the missing pixels of the irregularly sampled image into the regular grids. Then, the non-local block-based wavelet shrinkage denoising algorithm is applied, and the originally observed pixels are enforced. After iteration is performed, the denoising algorithm for non-edge areas is applied to acquire the final result. The experimental results show that the proposed method outperforms the conventional methods.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.167-174
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• 2008

The introduction of confocal microscopy makes it possible to observe the structural change of live neuronal cell. Neuro-degenerative disease, such as Alzheimer;s and Parkinson’s diseases are especially related to the morphological change of dendrite spine. That’s the reason for the study of segmentation and extraction from confocal microscope image. The difficulty comes from uneven intensity distribution and blurred boundary. Therefore, the image processing technique which can overcome these problems and extract the structural information should be suggested. In this paper, we propose robust structural information extracting technique with confocal microscopy images of dendrite in brain neurons. First, we apply the nonlinear diffusion filtering that enhance the boundary recognition. Second, we segment region of interest using iterative threshold selection. Third, we perform skeletonization based on Fast Marching Method that extracts centerline and boundary for analysing segmented structure. The result of the proposed method has been less sensitive to noise and has not been affected by rough boundary condition. Using this method shows more accurate and objective results.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.17-24
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• 2024

In this paper, we propose a highly secure technique to hide confidential data in image pixels using a quadruple encryption techniques. In the proposed technique, the boundary surface where the image outline exists and the flat surface with little change in pixel values are investigated. At the boundary of the image, in order to preserve the characteristics of the boundary, one bit of confidential data that has been multiply encrypted is spatially encrypted again in the LSB of the pixel located at the boundary to hide the confidential data. At the boundary of an image, in order to preserve the characteristics of the boundary, one bit of confidential data that is multiplely encrypted is hidden in the LSB of the pixel located at the boundary by spatially encrypting it. In pixels that are not on the border of the image but on a flat surface with little change in pixel value, 2-bit confidential data that is multiply encrypted is hidden in the lower 2 bits of the pixel using location-based encryption and spatial encryption techniques. When applying the proposed technique to hide confidential data, the image quality of the stego-image is up to 49.64dB, and the amount of confidential data hidden increases by up to 92.2% compared to the existing LSB method. Without an encryption key, the encrypted confidential data hidden in the stego-image cannot be extracted, and even if extracted, it cannot be decrypted, so the security of the confidential data hidden in the stego-image is maintained very strongly. The proposed technique can be effectively used to hide copyright information in general commercial images such as webtoons that do not require the use of reversible data hiding techniques.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.395-408
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• 2015

High-resolution satellite image mosaics are becoming increasingly important in the field of remote sensing image analysis as an essential image processing to create a large image constructed from several smaller images. In this paper, we present an automatic seamline extraction technique and the procedure to generate a mosaic image by this technique. For more effective seamline extraction in the overlap region of adjacent images, an NDVI-based seamline extraction technique is developed, which takes advantage of the computational time and memory. The Normalized Difference Vegetation Index(NDVI) is an index of plant "greeness" or photosynthetic activity that is employed to extract the initial seamline. The NDVI can divide into manmade region and natural region. The cost image is obtained by the canny edge detector and the buffering technique is used to extract the ranging cost image. The seamline is extracted by applying the Dijkstra algorithm to a cost image generated through the labeling process of the extracted edge information. Histogram matching is also conducted to alleviate radiometric distortion between adjacent images acquired at different time. In the experimental results using the KOMPSAT-2/3 satellite imagery, it is confirmed that the proposed method greatly reduces the visual discontinuity caused by geometric difference of adjacent images and the computation time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.6
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• pp.1-8
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• 2000

This paper describes an algorithm for semantic video object tracking using semi automatic method. In the semi automatic method, a user specifies an object of interest at the first frame and then the specified object is to be tracked in the remaining frames. The proposed algorithm consists of three steps: object boundary projection, uncertain area extraction, and boundary refinement. The object boundary is projected from the previous frame to the current frame using the motion estimation. And uncertain areas are extracted via two modules: Me error-test and color similarity test. Then, from extracted uncertain areas, the exact object boundary is obtained by boundary refinement. The simulation results show that the proposed video object extraction method provides efficient tracking results for various video sequences compared to the previous methods.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.99-104
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• 2002

Existing methods of object tracking use template matching, re-detection of object boundaries or motion information. The template matching method requires very long computation time. The re-detection of object boundaries may produce false edges. The method using motion information shows poor tracking performance in moving camera. In this paper, a robust object tracking algorithm is proposed, using projected motion and histogram intersection. The initial object image is constructed by selecting the regions of interest after image segmentation. From the selected object, the approximate displacement of the object is computed by using 1-dimensional intensity projection in horizontal and vortical direction. Based on the estimated displacement, various template masks are constructed for possible orientations and scales of the object. The best template is selected by using the modified histogram intersection method. The robustness of the proposed tracking algorithm has been verified by experimental results.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.22-25
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• 2009

본 논문은 기 구축된 환경부의 중분류 토지피복도를 올해 KOMPSAT-2 화상으로 갱신하기 위한 예비연구에서 분류결과의 정확도 평가를 중점적으로 나타낸다. KOMPSAT-2 화상기반의 중분류 토지피복도는 객체지향의 분류기법을 이용하였고, 경계선 수정의 경우 반자동 기법에 의해 제작되었다. 계통표집과 임의표집에 의한 Kappa 분석에서 계통 표집의 KHAT값은 0.81, 임의표집의 KHAT값은 0.89를 각각 가지므로 거의 완벽의 일치성을 표시한다. 따라서 전술한 지도화 방법을 통해 제작된 KOMPSAT-2 화상의 중분류 토지피복도는 이용자에게 토지피복정보의 신뢰성도 함께 제공한다.