• Journal of Korea Multimedia Society
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• v.16 no.11
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• pp.1288-1296
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• 2013

The prominent line at the singe image is the important fact for understanding spatial structure or estimating aesthetic scoring. According to this thesis, the abstraction of the background line helps analyzing vanishing point, reconstitution of 3 dimensions, and determining of image sloppiness. It also makes easy to calculate the rule of thirds. This thesis is composed of section hough transform mapping, prioritizing of the prominent line, and selection of the prominent line. These technologies are departmentalized to be applied abstraction of traffic lane, analyzing of building structure, abstraction of vanishing point, and abstraction of straight line documentation. This gives the choice that users are able to compose technology by considering characteristic of objects and luminous environment. This thesis also can be applied to abstract circle. The interval hough transform is able to select the number of prominent line which users want to abstract. It can analyze important prominent line numbers at the image and then abstract the lines, too. Results of prominent lines by experiments would be show at this thesis.

• Journal of Korea Multimedia Society
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• v.12 no.2
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• pp.244-256
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• 2009

This paper presents multiple watermarking method for the copyright protection and the prevention of illegal copying of mobile 3D contents. The proposed method embeds an unique watermark and a WCA watermark into the spatial and encryption domains of mobile 3D content based on anonymous Buyer-Seller watermarking protocol. The seller generates an unique watermark and embeds it into the distribution of vertex data of 3D content object. After receiving the encrypted watermark from WCA, the seller embeds it into the encrypted vertex data by using operator that satisfies the privacy homo morphic property. The proposed method was implemented using a mobile content tool, Power VR MBX and experimental results verified that the proposed method was capable of copyright protection and preventing illegal copying, as the watermarks were also accurately extracted in the case of geometrical attacks, such as noise addition, data accuracy variation, and data up/down scaling.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.3
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• pp.563-572
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• 2020

Tidal flats provide important indicators that inform the condition of the environment, so we need to monitor them systematically. Currently, the projects to monitor tidal flats by periodically observing the creatures in tidal flats are underway. Still, it is done in a way that people observe directly, so it is not systematic and efficient. In this paper, we propose a background modeling method for tidal flat images that can be applied to a system that automatically monitors creatures living in tidal flats using sensor network technology. The application of sensor network technology makes it difficult to collect enough images due to the limitation of transmission capacity. Therefore, in this paper, we propose a method to effectively model the background and generate foreground maps by reflecting the characteristics of tidal flat images in the situation where the number of images to be used for analysis is small. Experimental results show that the proposed method models the background of a tidal flat image easily and accurately.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.95-104
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• 2012

In the image captured by the camera in a moving vehicle, there exist various motions due to the change of background, motion of objects in the image that make difficult to extract a pure vibrational motion by the camera. In this paper, we suggest an image stabilization with the elimination of various motion components based on the classification of motions in the image by their characteristics. After the elimination of various local motions, images are compensated and stabilized with the global motion caused by the camera. Also, we suggest an accurate and fast image stabilization by excluding regions of little information based on block differences and edge densities.

• Journal of the Korea Society of Computer and Information
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• v.20 no.6
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• pp.87-97
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• 2015

An Aerial video summarization is not only the key to effective browsing video within a limited time, but also an embedded cue to efficiently congregative situation awareness acquired by unmanned aerial vehicle. Different with previous works, we utilize sensor operation mode of unmanned aerial vehicle, which is global, local, and focused surveillance mode in order for accurately summarizing the aerial video considering flight and surveillance/reconnaissance environments. In focused mode, we propose the moving-react tracking method which utilizes the partitioning motion vector and spatiotemporal saliency map to detect and track the interest moving object continuously. In our simulation result, the key frames are correctly detected for aerial video summarization according to the sensor operation mode of aerial vehicle and finally, we verify the efficiency of video summarization using the proposed mothed.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.8-14
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• 2005

The implementation of vision system using CCD camera which measures the earing rate of aluminium CAN is represented in this paper. In order to optimize the input image, the object of the input image is separated and the position of the image is calibrated. In the preprocessing, the definition of image is improved by the histogram equalization, and then the edges of the input image are detected by the Robert mask. The heights of the four ears and angles of the aluminium CAN are measured manually with the digital vernier calipers in industry. It takes 30 seconds to measure manually the height of one direction of the aluminium CAN at least three times. However, when the proposed system in this paper is applied, it takes 0.02 seconds only. In conclusion, the efficiency of the proposed system is higher than that of the system used in the industry.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.389-396
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• 2022

Deep Learning is based on a perceptron, and is currently being used in various fields such as image recognition, voice recognition, object detection, and drug development. Accordingly, a variety of learning algorithms have been proposed, and the number of neurons constituting a neural network varies greatly among researchers. This study analyzed the learning characteristics according to the number of neurons of the currently used SGD, momentum methods, AdaGrad, RMSProp, and Adam methods. To this end, a neural network was constructed with one input layer, three hidden layers, and one output layer. ReLU was applied to the activation function, cross entropy error (CEE) was applied to the loss function, and MNIST was used for the experimental dataset. As a result, it was concluded that the number of neurons 100-300, the algorithm Adam, and the number of learning (iteraction) 200 would be the most efficient in deep learning learning. This study will provide implications for the algorithm to be developed and the reference value of the number of neurons given new learning data in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.165-167
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• 2022

The proportion of cat cats among companion animals has been increasing at an average annual rate of 25.4% since 2012. Cats have strong wildness compared to dogs, so they have a characteristic of hiding diseases well. Therefore, when the guardian finds out that the cat has a disease, the disease may have already worsened. Symptoms such as anorexia (eating avoidance), vomiting, diarrhea, polydipsia, and polyuria in cats are some of the symptoms that appear in cat diseases such as diabetes, hyperthyroidism, renal failure, and panleukopenia. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia (drinking a lot of water), polyuria (a large amount of urine), and frequent urination (urinating frequently) more quickly. In this paper, 1) Efficient version of DeepLabCut for posture prediction running on an artificial intelligence server, 2) yolov4 for object detection, and 3) LSTM are used for behavior prediction. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the main server system.