• Journal of Korea Society of Industrial Information Systems
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• v.6 no.1
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• pp.33-38
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• 2001

In this paper, we present an image retrieval system using shape features. The preprocessing to gain shape feature includes edge extraction using chain code. The shape features consist of center of mass, standard deviation, ratio of major axis and minor axis length. The similarity is estimated as comparing the features of query image with the features of images in database. Thus, the candidates of images are retrieved according to the order of similarity. The result of an experimentation is dullness for scale, rotation and translation. We evaluate the performance of shape features for image retrieval on a database with over 170 images. The Recall and the Precision is each 0.72 and 0.83 in the result of average experiment. So the proposed method is presented useful method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4866-4888
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• 2020

One major and time-consuming task in fish production is obtaining an accurate estimate of the number of fish produced. In most Nigerian farms, fish counting is performed manually. Digital image processing (DIP) is an inexpensive solution, but its accuracy is affected by noise, overlapping fish, and interfering objects. This study developed a catfish recognition and counting algorithm that introduces detection before counting and consists of six steps: image acquisition, pre-processing, segmentation, feature extraction, recognition, and counting. Images were acquired and pre-processed. The segmentation was performed by applying three methods: image binarization using Otsu thresholding, morphological operations using fill hole, dilation, and opening operations, and boundary segmentation using edge detection. The boundary features were extracted using a chain code algorithm and Fourier descriptors (CH-FD), which were used to train an artificial neural network (ANN) to perform the recognition. The new counting approach, based on the geometry of the fish, was applied to determine the number of fish and was found to be suitable for counting fish of any size and handling overlap. The accuracies of the segmentation algorithm, boundary pixel and Fourier descriptors (BD-FD), and the proposed CH-FD method were 90.34%, 96.6%, and 100% respectively. The proposed counting algorithm demonstrated 100% accuracy.

• Journal of Korea Multimedia Society
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• v.17 no.2
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• pp.143-151
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• 2014

In images degraded by bad weather, edges representing object boundaries become weak and faint. In this paper we present an image enhancement method, which increases image visibility by making edges as clear as possible. First, we choose edge candidate regions by finding local maxima and minima in an image intensity field, and then build a histogram using image intensities of pixels located at the two sides of candidate edges. Second, we decompose this histogram into multiple modes, which are determined by local minima in the histogram. Once modes are computed, we find modes connected by edges in the image intensity field and build link chains of connected modes. Finally we choose the longest link chain of modes and make the distances between every connected modes as large as possible. The darkest mode and the brightest mode should be within the image intensity range. This stretch makes edges clear and increases image visibility. Experiments show that the proposed method real-time enhances images degraded by bad weather as good as well known time-consuming methods.

• The Journal of the Korea Contents Association
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• v.10 no.10
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• pp.1-8
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• 2010

Recently, the character image processing technology using portable device camera image at home and abroad are actively conducted, but Practical use are lower rate because of accuracy and time-consuming process problems. In this paper, we propose the license plate recognition method based on geometric information from portable device camera image. In the extracted license plate region we recognize characters using the chain code and the Thickness information through the cumulative projected edge after performing the pre-processing work considering the angle difference, the contrast enhancement and the low resolution from portable device camera image. The proposed algorithm is effective and accurate recognition by light and reducing the processing time. And, the results from the character recognition success rate was 95%. In the future, we will research about license plate recognition algorithm using long distance image or added motion blur image.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.201-208
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• 2010

The classical iterated hash function is vulnerable to a multi-collision attack. Gauravaram et al. proposed 3C and 3C+ hash functions, in which an accumulation chain is added to usual Merkle-Damgard changing. Their goal is to design composition schemes resistant to generic attacks of Joux's type, but Joscak and Tuma have shown that 3C and 3C+ schemes are not better than Merkle-Damgard scheme in term of security against multi-collision attacks under some mild assumptions. In this dissertation, in order to increase security of 3C hash function, we proposed secure double pipe hash function which was effectively using XOR and XNOR operations per blocks of message. We seek to improve on the work of Lucks in a way. Proposed secure double pipe hash function takes resistance to multi-block collision, fixed point and pre-image attacks.

• The Journal of the Korea Contents Association
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• v.14 no.12
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• pp.545-554
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• 2014

In this paper, we propose online Chinese character learning machine with a depth camera, where a system presents a Chinese character on a screen and a user is supposed to draw the presented Chinese character by his or her hand gesture. We develop the hand tracking method and suggest the adjusted chain code to represent constituent strokes of a Chinese character. For hand tracking, a fingertip is detected and verified. The adjusted chain code is designed to contain the information on order and relative length of each constituent stroke as well as the information on the directional variation of sample points. Such information is very efficient for a real-time match process and checking incorrectly drawn parts of a stroke.

• Journal of Science and Technology Studies
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• v.11 no.2
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• pp.67-96
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• 2011

Studies in scientific visualization have disclosed a visual chain among many scientific visualizations, which starts from the photographs that have many details to diagrams that enable scientists to make specific claims due to their abstract characters. Located at both ends of the visual chain, photographs and diagrams are regarded as being different kinds and having different characteristics. The photographs - or microphotographs to be precise - that this paper discusses, however, had been removed of unnecessary details and were prepared with carful attention to illustrative functions that diagrams usually perform. Following microphotographic changes in a Korean laboratory, this article shows that the knowledge of specimen preparation was transmitted from an American leading group to the Korean laboratory through a direct contact, and that with this, the technique of taking microphotographs of the laboratory was much improved. The specimen preparation method is, however, a tacit knowledge that is invisible in both group's papers. This article argues that the method of specimen preparation is the driving force that made the microphotographs act like carefully prepared diagrams and acquire objectivity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.13-19
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• 2019

The accuracy of machine learning is greatly affected by amount of learning data and quality of data. Collecting existing Web-based learning data has danger that data unrelated to actual learning can be collected, and it is impossible to secure data transparency. In this paper, we propose a method for collecting data directly in parallel by blocks in a block - chain structure, and comparing the data collected by each block with data in other blocks to select only good data. In the proposed system, each block shares data with each other through a chain of blocks, utilizes the All-reduce structure of Parallel-SGD to select only good quality data through comparison with other block data to construct a learning data set. Also, in order to verify the performance of the proposed architecture, we verify that the original image is only good data among the modulated images using the existing benchmark data set.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.11
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• pp.1867-1871
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• 1989

One of the most common problems in pattern recognition and image processing is filling the interior of a region when its contour is given. The existing algorithms of the filling are parity check technique, seeding technique, and technique based on chain coding the boundaries. In this paper, a very simple but effective technique for filling the interior of bounded region is proposed. This algorithm is based on the information of binary-coded boundary direction and covers some of the drawbacks reported in the earlier relevant works.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1986.10a
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• pp.53-55
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• 1986

The edge detection system makes use or 3*3 compass gradient masks, which are well suited for digital implementation. Edge angles are quantized to eight equally spaced directions, suitable for chain coding of contours. Use of edge direction msp improves the simple thresholding of gradient modulus image. The concept of local connectivity of the edge direction map is useful improving the performance of this method as well as other edge operators such as Kirsch and Sobel.