• Journal of Korea Society of Industrial Information Systems
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• v.12 no.3
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• pp.132-140
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• 2007

The quality of the camera image is worse than that of the scanner image because of lighting variation and inaccurate focus. This paper proposes a binarization method for camera-based document recognition, which is tolerant to low-quality camera images. Based on an existing method reported to be effective in previous evaluations, we enhanced the adaptability to the image with a low contrast due to low intensity and inaccurate focus. Furthermore, applying an additional small-size window in the binarization process, it is effective to extract the fine detail of character structure, which is often degraded by conventional methods. In experiments, we applied the proposed method as well as other methods to a document recognizer and compared the performance for many cm images. The result showed the proposed method is effective for recognition of document images captured by the camera.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.7
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• pp.569-581
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• 1989

This paper deals with a tracking algorithm based on integral projection which tracks moving targets with varying brightness and size. An adaptive windowing technique is employed to reduce the sensitivity of the system to the complex background image and also to reduce the computational load. The threshold value is determined by considering both the size and the threshold value of the brightness intensity of the recognized target obtained in the previous processing step. Window position is estimated by using the information of the velocity and acceleration of the target. And integral projection is applied to find the position of the target in the window accurately. Experimental results show that moving targets with varying brightness and size can be tracked properly in noisy environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9A
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• pp.905-915
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• 2007

This paper proposes a filter-based algorithm to adaptively adjust the contention window in IEEE 802.11 DCF. The proposed mechanism is focused on the general and realistic environments that have various conditions regarding to noise, media types and network load. For this flexible adaptation, Filter-based DCF(FDCF) takes a more realistic policy such as median filter concept in the image processing technologies. We can handle these various environments by adjusting the contention window size according to the result of filtering based on history-buffer. We can ignore temporarily and randomly occurred transmission failures due to noise errors and collisions in noisy environments. In addition, by changing the reference number and history-buffer size, FDCF can be extended as a general solution including previous proposed mechanism. We have confirmed that the proposed mechanism can achieve the better performance than those of previous researches in aspects of the throughput and the delay in the realistic environments.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.4
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• pp.611-617
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• 2004

Pixel classification is one of basic image processing issues. The general characteristics of the pixels belonging to various classes are discussed and the radical principles of pixel classification are given. At the same time. a pixel classification scheme based on image direction measure is proposed. As a typical application instance of pixel classification, an adaptive multi-level median filter is presented. An image can be classified into two types of areas by using the direction information measure, that is. smooth area and edge area. Single direction multi-level median filter is used in smooth area. and multi-direction multi-level median filter is taken in the other type of area. What's more. an adaptive mechanism is proposed to adjust the type of the filters and the size of filter window. As a result. we get a better trade-off between preserving details and noise filtering.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.445-452
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• 2019

In this study, parallel processing codes of k-means clustering algorithm were developed and implemented in a PC-cluster for unsupervised classification of large satellite images. We implemented intra-node code using multicores of CPU (Central Processing Unit) based on OpenMP (Open Multi-Processing), inter-nodes code using a PC-cluster based on message passing interface, and hybrid code using both. The PC-cluster consists of one master node and eight slave nodes, and each node is equipped with eight multicores. Two operating systems, Microsoft Windows and Canonical Ubuntu, were installed in the PC-cluster in turn and tested to compare parallel processing performance. Two multispectral satellite images were tested, which are a medium-capacity LANDSAT 8 OLI (Operational Land Imager) image and a high-capacity Sentinel 2A image. To evaluate the performance of parallel processing, speedup and efficiency were measured. Overall, the speedup was over N / 2 and the efficiency was over 0.5. From the comparison of the two operating systems, the Ubuntu system showed two to three times faster performance. To confirm that the results of the sequential and parallel processing coincide with the other, the center value of each band and the number of classified pixels were compared, and result images were examined by pixel to pixel comparison. It was found that care should be taken to avoid false sharing of OpenMP in intra-node implementation. To process large satellite images in a PC-cluster, code and hardware should be designed to reduce performance degradation caused by file I / O. Also, it was found that performance can differ depending on the operating system installed in a PC-cluster.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1495-1507
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• 1997

Among a number of approaches to text compression, adaptive dictionary schemes based on a sliding window have been very frequently used due to their high performance. The LZ77 algorithm is the most efficient algorithm which implements such adaptive schemes for the practical use of text compression. This paperpresents a VLSI architecture designed for processing the LZ77 algorithm in parallel. Compared with the other VLSI architectures developed so far, the proposed architecture provides the more viable solution to high performance with regard to its throughput, efficient implementation of the VLSI systolic arrays, and hardware scalability. Indeed, without being affected by the size of the sliding window, our system has the complexity of O(N) for both the compression and decompression and also requires small wafer area, where N is the size of the input text.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.5
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• pp.90-97
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• 2001

An electronic speckle pattern interferometry (ESPI) system for measuring tensile properties under micro-tensile testing has been developed. The system consists of an optical system and an image processing system. In the optical system, optical components for measurement of in-plane deformation are arranged on the path of He-Ne laser. In the image processing system, the window-based program for acquiring speckle pattern interferometric image was developed and deformation in a small specimen is continuously evaluated during the test. Using this system, tensile strain of copper foil was measured during tensile testing. Tensile specimen had the thickness and width of 22 and 500 ${\mu}{\textrm}{m}$, respectively. Tensile properties, including the elastic modulus, yielding strength and tensile strength, of the copper were evaluated and also plastic exponent and coefficient in the Ramberg-Osgood relationship were evaluated from the stress-strain curve.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.65-70
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• 2013

Recently, the field of computer vision has been actively researched through digital image which can be easily generated as the development and expansion of digital camera technology. Especially, research that extracts and utilizes the feature in image has been actively carried out. The image stitching is a method that creates the high resolution image using features extract and match. Image stitching can be widely used in military and medical purposes as well as in variety fields of real life. In this paper, we have proposed efficient image stitching method using fast feature descriptor extraction and matching based on SURF algorithm. It can be accurately, and quickly found matching point by reduction of dimension of feature descriptor. The feature descriptor is generated by classifying of unnecessary minutiae in extracted features. To reduce the computational time and efficient match feature, we have reduced dimension of the descriptor and expanded orientation window. In our results, the processing time of feature matching and image stitching are faster than previous algorithms, and also that method can make natural-looking stitched image.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.517-520
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• 2003

Commercial video scope use CCD sensor and frame grabber for image capture and A/D interface but application limited by input resolution and high cost. In this paper we introduce portable video scope using CMOS sensor, USB pen and tuner card (low frame grabber) in place of commercial CCD sensor and frame grabber. Our video scope serves as an essential link between advancing commercial technology and research, providing cost effective solutions for educational, engineering and medical applications across an entire spectrum of needs. The software implementation is done using Direct Show in second version after initial trials using First version VFW (video for window), which gave very low frame rate. Our video scope operates on windows 98, ME, XP, 2000. The drawback of our video scope is crossover problem in output images caused due to interpolation, which has to be rectified for more efficient performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.6
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• pp.1482-1489
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• 1998

This paper aims to extract characteristics of the spectrum of fingerprint image and to apply them to image enhancement techniques in spatial frequency domain. Based on 1$\times$64 window as a processing unit and the different record lengths(32, 16, 8), the estimate of power spectrum density for each length was made. Each acquired spectrum characteristics was applied to the re-synthesis process of the fingerprint image, an improved gray scale image was obtained. In order to select an optimal predictor and the Huffman table for the fingerprint iamge, the lossless JPEG algorithm was used. Experiments were performed for extracting distribution characteristics for the each of 7 predictors from the fingerprint image and modeling processes, and the result was applied to the data compression algorithm and the selection of the optimal predictor.