• International Journal of Advanced Culture Technology
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• v.11 no.3
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• pp.65-77
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• 2023

Chinese martial arts culture is a kind of Chinese kung fu culture, a cultural category that uses martial arts kung fu for chivalry and justice. Chinese martial arts MMORPG online game is the embodiment of Chinese martial arts culture in online games, which is a unique Chinese online game. The image of beggar chivalry is a special chivalrous image in Chinese martial arts culture, and in the top 3 martial arts MMORPG online games, all of them have the image of beggar chivalry, which shows that this image has a wide player base. The Q methodology is an approach that endeavors to discover complex issues in human subjectivity, unlike existing empirical studies. In order to determine the type of beggar chivalry image preference of the game players, 32 beggar chivalry images were selected in the study and three types of beggar chivalry images were found through the Q method: Type 1 is the type of gorgeous and noble beggar chivalry; Type 2 is a competent type and is good at fighting the beggar's chivalry; and Type 3 is comparable relatively refined type. The result of this study is that the image of beggar chivalry preferred by game players is the opposite of the traditional Chinese image of beggar chivalry. The traditional image of beggar is the image of wearing plain and begging in the street, but the image of beggar chivalry that is liked in online games is luxurious, noble, exquisite and about the image of good at fighting. This research result has some value and significance in the development and design of beggar chivalrous image in future martial arts MMORPG online games.

• The Journal of Korea Robotics Society
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• v.10 no.3
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• pp.146-153
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• 2015

In order to contain as much information as possible in a single image, a wide FOV(Field-Of-View) imaging system is required. The catadioptric imaging system with hyperbolic cylinder mirror can acquire over 180 degree horizontal FOV realtime panorama image by using a conventional camera. Because the hyperbolic cylinder mirror has a curved surface in horizontal axis, the original image acquired from the imaging system has the geometrical distortion, which requires the image processing algorithm for reconstruction. In this paper, the image reconstruction algorithms for two cases are studied: (1) to obtain an image with uniform angular resolution and (2) to obtain horizontally rectilinear image. The image acquisition model of the hyperbolic cylinder mirror imaging system is analyzed by the geometrical optics and the image reconstruction algorithms are proposed based on the image acquisition model. To show the validity of the proposed algorithms, experiments are carried out and presented in this paper. The experimental results show that the reconstructed images have a uniform angular resolution and a rectilinear form in horizontal axis, which are natural to human.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.617-625
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• 2017

In this paper, an effective reversible data embedding algorithm was proposed to embed secrete data into image. In the proposed algorithm, prediction image is generated by accurately predicting pixel values using local similarity existing in image, difference sequence is generated using the generated prediction image and original cover image, and then histogram shift technique is applied to create a stego-image with secrete data hidden. Applying the proposed algorithm, secrete data can be extracted from the stego-image and the original cover image can be restored without loss. Experimental results show that it is possible to embed more secrete data into cover image than APD algorithm by applying the proposed algorithm.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.84-93
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• 2015

This study is for the development of Cover Glass Grinding Processing System. This system is developed for manufacturing a mass product system grinding cover glasses with highly precise mechanism, and we improved resulted quality. In the development process, we developed a complete process technology through mechanical design, image processing technology, spindle control, mark identification algorithm etc. With this cover glass grinding development, we could developed process technology, image processing technology, organization mechanisms and control algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1355-1360
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• 2005

In this paper, we approach the problem of image filter design automation using a kind of intrinsic evolvable hardware architecture. For the purpose of implementing the intrinsic evolution process in a common FPGA chip and evolving a complicated digital circuit system-image filter, the design automation system employs the reconfigurable circuit architecture as the reconfigurable component of the EHW. The reconfigurable circuit architecture is inspired by the Cartesian Genetic Programming and the functional level evolution. To increase the speed of the hardware evolution, the whole evolvable hardware system which consists of evolution algorithm unit, fitness value calculation unit and reconfigurable unit are implemented by a commercial FPGA chip. The Celoxica RC1000 card which is fitted with a Xilinx Virtex xcv2000E FPGA chip is employed as the experiment platform. As the result, we conclude the terms of the synthesis report of the image filter design automation system and hardware evolution speed in the Celoxica RC1000 card. The evolved image filter is also compared with the conventional image filter form the point of filtered image quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.249-268
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• 2014

Relevance feedback is an effective tool to bridge the gap between superficial image contents and medically-relevant sense in content-based medical image retrieval. In this paper, we propose an interactive medical image search framework based on pairwise constraint propagation. The basic idea is to obtain pairwise constraints from user feedback and propagate them to the entire image set to reconstruct the similarity matrix, and then rank medical images on this new manifold. In contrast to most of the algorithms that only concern manifold structure, the proposed method integrates pairwise constraint information in a feedback procedure and resolves the small sample size and the asymmetrical training typically in relevance feedback. We also introduce a long-term feedback strategy for our retrieval tasks. Experiments on two medical image datasets indicate the proposed approach can significantly improve the performance of medical image retrieval. The experiments also indicate that the proposed approach outperforms previous relevance feedback models.

• Journal of Korea Multimedia Society
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• v.25 no.9
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• pp.1266-1272
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• 2022

With the recent development of computer vision technology, image processing-based mechanical devices are being developed to realize autonomous driving. The camera-taken images of image processing-based machines are invisible due to scattering and absorption of light in foggy conditions. This lowers the object recognition rate and causes malfunction. The safety of the technology is very important because the malfunction of autonomous driving leads to human casualties. In order to increase the stability of the technology, it is necessary to apply an efficient haze removal algorithm to the camera. In the conventional haze removal method, since the haze removal operation is performed regardless of the haze concentration of the input image, excessive haze is removed and the quality of the resulting image is deteriorated. In this paper, we propose an automatic haze removal method that removes haze according to the haze density of the input image by applying Ngo's Haziness Degree Evaluator (HDE) to Kim's haze removal algorithm using Hazy Particle Map. The proposed haze removal method removes the haze according to the haze concentration of the input image, thereby preventing the quality degradation of the input image that does not require haze removal and solving the problem of excessive haze removal. The superiority of the proposed haze removal method is verified through qualitative and quantitative evaluation.

• International Journal of Quality Innovation
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• v.5 no.1
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• pp.68-84
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• 2004

The measured values of a same object should remain constant regardless of the object's position in the image. In other words, its measured values should not vary as its position in the image changes. However, lens' image distortion, heterogeneous light source, varied angle between the measuring apparatus and the object, and different surroundings where the testing is set up will all cause variation in the measurement of the object when the object's position in the image changes. This research attempts to compensate the machine vision image distortion caused by the object's position in the image by developing the compensation table. The compensation is accomplished by facilitating users to obtain the correcting object and serves the objective of improving the precision of measurement.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.96-101
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• 2001

The development of a new experimental method is required to easily observe the growth behavior of fatigue cracks. To satisfy the requirement, an image processing technique was introduced to fatigue testing. The length of surface fatigue crack could be successfully measured by the image processing system. At first, the image data of cracks were stored into the computer while the cyclic loading was interrupted. After testing, crack length was determined using image processing software which was developed by ourselves. Block matching method was applied to the detection of surface fatigue cracks. By comparing the data measured by image processing system with the data measured by manual measurement with a microscope, the effectiveness of the image processing system was established. If the proposed method is used to monitor and observe the crack growth behavior automatically, the time and efforts for fatigue test could be dramatically reduced.

• Journal of Computing Science and Engineering
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• v.11 no.1
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• pp.1-8
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• 2017

Naive Bayes nearest neighbor (NBNN) is a simple image classifier based on identifying nearest neighbors. NBNN uses original image descriptors (e.g., SIFTs) without vector quantization for preserving the discriminative power of descriptors and has a powerful generalization characteristic. However, it has a distinct disadvantage. Its memory requirement can be prohibitively high while processing a large amount of data. To deal with this problem, we apply a spherical hashing binary code embedding technique, to compactly encode data without significantly losing classification accuracy. We also propose using an inverted index to identify nearest neighbors among binarized image descriptors. To demonstrate the benefits of our method, we apply our method to two existing NBNN techniques with an image dataset. By using 64 bit length, we are able to reduce memory 16 times with higher runtime performance and no significant loss of classification accuracy. This result is achieved by our compact encoding scheme for image descriptors without losing much information from original image descriptors.