• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.444-447
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• 2008

In this paper, we proposed the recognition system of car license plates to mitigate traffic problems. The processing sequence of the proposed algorithm is as follows. At first, a license plate segment is extracted from an acquired car image using morphological features and color information, and noises are eliminated from the extracted license plate segment using line scan algorithm and Grassfire algorithm, and then individual codes are extracted from the license plate segment using edge tracking algorithm. Finally the extracted individual codes are recognized by an FCM algorithm. In order to evaluate performance of segment extraction and code recognition of the proposed method, we used 100 car images for experiment. In the results, we could verify the proposed method is more effective and recognition performance is improved in comparison with conventional car license plate recognition methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1095-1109
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• 2022

Along with the popularity of GPS system and smart cell phone, trajectories of pedestrians or vehicles are recorded at any time. The great amount of works had been carried out in order to discover traffic paradigms or other regular patterns buried in the huge trajectory dataset. The core of the mining algorithm is how to evaluate the similarity, that is, the "distance", between trajectories appropriately, then the mining results will be accordance to the reality. Euclidean distance is commonly used in the lots of existed algorithms to measure the similarity, however, the trend of trajectories is usually ignored during the measurement. In this paper, a novel segment transform distance (STD) algorithm is proposed, in which a rule system of line segment transformation is established. The similarity of two-line segments is quantified by the cost of line segment transformation. Further, an improvement of STD, named ST-DTW, is advanced with the use of the traditional method dynamic time warping algorithm (DTW), accelerating the speed of calculating STD. The experimental results show that the error rate of ST-DTW algorithm is 53.97%, which is lower than that of the LCSS algorithm. Besides, all the weights of factors could be adjusted dynamically, making the algorithm suitable for various kinds of applications.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.177-181
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• 1999

This paper presents an algorithm for building detection from aerial image using segment measure function and line relation. In the detection algorithm proposed, edge detection, linear approximation and line linking are used and then line measure function is applied to each line segment in order to improve the accuracy of linear approximation. Parallelisms, orthogonalities are applied to the extracted liner segments to extract building. The algorithm was applied to aerial image and the buildings were accurately detected.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.406-420
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• 2020

In order to make up the deficiencies of the existing research results which cannot effectively deal with the nearest neighbor query based on the line segments in obstacle space, the k nearest neighbor query method of line segment in obstacle space is proposed and the STA_OLkNN algorithm under the circumstance of static obstacle data set is put forward. The query process is divided into two stages, including the filtering process and refining process. In the filtration process, according to the properties of the line segment Voronoi diagram, the corresponding pruning rules are proposed and the filtering algorithm is presented. In the refining process, according to the relationship of the position between the line segments, the corresponding distance expression method is put forward and the final result is obtained by comparing the distance. Theoretical research and experimental results show that the proposed algorithm can effectively deal with the problem of k nearest neighbor query of the line segment in the obstacle environment.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.126-129
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• 2008

In this paper, we proposed a method extracting an object from background of the satellite image. The image segmentation techniques have been widely studied for the technology to segment image and to synthesis segment object with other images. Proposed algorithm is to perform the edge detection of a selected object using genetic algorithm. We segment region of object based on detection edge using watershed algorithm. We separated background and object in indefinite region using gradual region merge from segment object. And, we make GUI for the application of the proposed algorithm to various tests. To demonstrate the effectiveness of the proposed method, several analysis on the satellite images are performed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2223-2230
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• 2011

ECG is used to diagnose heart diseases such as myocardial ischemia, arrhythmia and myocardial infarction. Particularly, myocardial ischemia causes the shape change of the ST segment, this change is transient and may occur without symptoms. So it is important to detect the transient change of ST segment through long term monitoring. ST segment classification algorithm for making diagnosis myocardial ischemia is presented in this paper. The first step in the ST segment shape classification process is to detect R wave point and feature points based adaptive threshold and window. And then, the suggested algorithm detects the ST level change, To classify the ST segment shape, the suggested algorithm uses the slope values of the four points between the S and T wave. The ECG data in the European ST-T database were used to verify the performance of the developed algorithm. The best correct rate was 99.40% and the worst correct rate was 68.48%.

• Journal of applied mathematics & informatics
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• v.7 no.2
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• pp.629-640
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• 2000

this paper present an efficient line-drawing algorithm that reduces the amount of space required, Because of its efficiency , this line-drawing algorithm is faster than the Bresenham algorithm or the recursive bisection method. this efficiency was achieved through a new data structure; namely , the modified segment tree (MST). Using the modified segment tree and the distribution rule suggested in this paper, we dra lines without generating the recursive calls used in [3] and without creating the binary operation used in [4]. we also show that line accuracy improves in proportion to the display resolution . In practice, we can significantly improve the algorithm's performance with respect to time and space, This improvement offer an increase in speed, specially with lines at or near horizontal, diagonal. or vertical ; that is, this algorithm requires the time complexity of (n) and the space complexity O(2k+1), where n is the number of pixels and k is a level of the modified segment tree.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.241-241
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• 2000

In this Paper, we present a new efficient algorithm that can segment an object in the image. There are many algorithms for segmentation and many studies for criteria or threshold value. But, if the environment or brightness is changed, their would not be suitable. Accordingly, we apply a clustering algorithm for adopting and compensating environmental factors. And applying labeling method, we try arranging segment by the similarity that calculated with the fuzzy algorithm. we also present simulations for searching an object and show that the algorithm is somewhat more efficient than the other algorithm.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.129-131
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• 2004

Elliptic Curve Cryptography (ECC) coprocessors support massive scalar multiplications of a point. We research the design for multi-segment multipliers in fixed-size ECC coprocessors using the multi-segment Karatsuba algorithm on GF($2^m$). ECC coprocessors of the proposed multiplier is verified on the SoC-design verification kit which embeds ALTERA EXCALIBUR FPGAs. As a result of our experiment, the multi-segment Karatsuba multiplier, which has more efficient performance about twice times than the traditional multi-segment multiplier, can be implemented as adding few H/W resources. Therefore the multi-segment Karatsuba multiplier which satisfies performance for the cryptographic algorithm, is adequate for a low cost embedded system, and is implemented in the minimum area.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.283-289
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• 2006

The present image segmentation is what user want to segment image and has been studied for technology in composition of segment object with other images. In this paper, we propose a method of novel semi-automatic image segmentation using gradual region merging and genetic algorithm. Proposed algorithm is edge detection of object using genetic algorithm after selecting object which user want. We segment region of object which user want to based on detection edge using watershed algorithm. We separated background and object in indefinite region using gradual region merge from Segment object. And, we have applicable value which user want by making interface based on GUI for efficient perform of algorithm development. In the experiments, we analyzed various images for proving superiority of the proposed method.