• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1375-1378
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• 1987

In this paper, an efficient data compression algorithm for binary image is proposed. This algorithm makes use of the fact that boundaries contain all the information about such images. The compression efficiency is then further increased by efficient coding of Boundary Information Matrix. The comparison of performance with modified Huffman coding was made by a computer simulation with some images. The results of simulation showed that the proposed algorithm was more efficient than modified Huffman code.

• Journal of Biosystems Engineering
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• v.24 no.1
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• pp.51-58
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• 1999

A color image processing algorithm was developed to assist the robotic plug-seedling transplanter. The algorithm was designed to identify and locate empty cells in the seedling tray. The image of pepper seedling tray was segmented into regions of plant, frame and soil using thresholding technique which utilized HSI or RGB color characteristics of each region. The detection algorithm was able to successfully identify empty cells and locate their two-dimensional location. The overall success rate of the algorithm was about 88%.

• Journal of the Optical Society of Korea
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• v.18 no.4
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• pp.341-344
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• 2014

This study proposes a modified sub-aperture stitching algorithm, which uses an image sharpening algorithm and particle swarm optimization to improve the stitching accuracy. In sub-aperture stitching interferometers with high positional accuracy, the high-frequency components of measurements are more important than the low-frequency components when compensating for position errors using a sub-aperture stitching algorithm. Thus we use image sharpening algorithms to strengthen the high-frequency components of measurements. When using image sharpening algorithms, sub-aperture stitching algorithms based on the least-squares method easily become trapped at locally optimal solutions. However, particle swarm optimization is less likely to become trapped at a locally optimal solution, thus we utilized this method to develop a more robust algorithm. The results of simulations showed that our algorithm compensated for position errors more effectively than the existing algorithm. An experimental comparison with full aperture-testing results demonstrated the validity of the new algorithm.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.11a
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• pp.163-166
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• 2000

This paper presents an image processing algorithm which gives an sketch effect on the real image taken by CCD camera. The essence of the technique is the expression of shading by the line touch. Several line patterns are developed to emulate pencil drawings, fusains, Indian ink paintings. This algorithm is expected to be used for computer portraits, character development, and souvenirs.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.5
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• pp.601-608
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• 2014

In this study we propose an image denoising algorithm appropriate for mobile smart phone equipped with limited computing ability, which has better performance and at the same time comparable quality comparing with previous studies. The proposed image denoising algorithm for mobile smart phone cameras in low level light environment reduces computational complexity and also prevents edge smoothing by extracting just Gaussian noises from the noisy input image. According to the experiment result, we verified that our algorithm has much better PSNR value than methods applying mean filter or median filter. Also the result image from our algorithm has better clear quality since it preserves edges while smoothing input image. Moreover, the suggested algorithm reduces computational complexity about 52% compared to the method applying original Laplacian mask computation, and we verified that our algorithm has good denoising quality by implementing the algorithm in Android smart phone.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.479-486
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• 2016

In this paper, the algorithm which can convert a 2D image into a 3D Model will be discussed. The 2D picture drawn by a user is scanned for image processing. The Canny algorithm is employed to find the contour. The waterfront algorithm is proposed to find foreground image area. The foreground area is segmented to decompose the complex shapes into simple shapes. Then, simple segmented foreground image is converted into 3D model to become a complex 3D model. The 3D conversion formular used in this paper is also discussed. The generated 3D model data will be useful for 3D animation and other 3D contents creation.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1748-1751
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• 1991

Generally, we can't acquire clear boundary or area from an image having obscure boundary like allergy image by using Sobel or Lapalace operator. Also, when the image not uniform in some part of a image in brightness, there are difficulties to use the global operator such as histogram, for the contour line doesn't have the same grey level. In this paper, we will propose an algorithm to improve those difficulties. The main idea of the algorithm is that we divide the image into many rectangular parts like a chess board, calculate the average of each part, and decide the local threshold for each pixel on the calculated value. In experiment, we can get the contour and area by this algorithm which is much like to the contour and area measured by a doctor. Also, This algorithm has many advantages such as short processing time and little influences of noises and can be used in the robot vision, etc..

• Journal of Korea Multimedia Society
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• v.18 no.10
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• pp.1180-1188
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• 2015

In this paper, a parallel cell contour line extraction algorithm using CUDA, which has no inner contour lines, is proposed. The contour of a cell is very important in a cell image analysis. It could be obtained by a conventional serial contour tracing algorithm or parallel morphology operation. However, the cell image has various damages in acquisition or dyeing process. They could be turn into several inner contours, which make a cell image analysis difficult. The proposed algorithm introduces a min-max coordinates table into each CUDA thread block, and removes the inner contour in parallel. It is 4.1 to 7.6 times faster than a conventional serial contour tracing algorithm.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.858-863
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• 2018

In this paper, we propose and implement a multi-level convolutional neural network (CNN) algorithm to identify the sexually explicit and lewdness of various image files, and verify its effectiveness by using unauthorized image files generated in the actual military. The proposed algorithm increases the accuracy by applying the convolutional artificial neural network step by step to minimize classification error between similar categories. Experimental data have categorized 20,005 images in the real field into 6 authorization categories and 11 non-authorization categories. Experimental results show that the overall detection rate is 99.51% for the image files. In particular, the excellence of the proposed algorithm is verified through reducing the identification error rate between similar categories by 64.87% compared with the general CNN algorithm.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.39-39
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• 2011

This study presents an effective vision-based system for cable bridge damage detection. In theory, cable bridges need to be inspected the outer as well as the inner part. Starting from August 2010, a new research project supported by Korea Ministry of Land, Transportation Maritime Affairs(MLTM) was initiated focusing on the damage detection of cable system. In this study, only the surface damage detection algorithm based on a vision-based system will be focused on, an overview of the vision-based cable damage detection is given in Fig. 1. Basically, the algorithm combines the image enhancement technique with principal component analysis(PCA) to detect damage on cable surfaces. In more detail, the input image from a camera is processed with image enhancement technique to improve image quality, and then it is projected into PCA sub-space. Finally, the Mahalanobis square distance is used for pattern recognition. The algorithm was verified through laboratory tests on three types of cable surface. The algorithm gave very good results, and the next step of this study is to implement the algorithm for real cable bridges.