• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1015-1023
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• 2022

The Entry-Descent-Landing process of a lander involves many environmental and technical challenges. To solve these problems, recently, terrestrial relative navigation (TRN) technology has been essential for landers. TRN is a technology for estimating the position and attitude of a lander by comparing Inertial Measurement Unit (IMU) data and image data collected from a descending lander with pre-built reference data. In this paper, we present a method for generating descent dataset and extracting landmarks, which are key elements for developing TRN technologies to be used on Mars. The proposed method generates IMU data of a descending lander using a simulated Mars landing trajectory and generates descent images from high-resolution ortho-map and digital elevation map through a ray tracing technique. Landmark extraction is performed by an area-based extraction method due to the low-textured surfaces on Mars. In addition, search area reduction is carried out to improve matching accuracy and speed. The performance evaluation result for the descent dataset generation method showed that the proposed method can generate images that satisfy the imaging geometry. The performance evaluation result for the landmark extraction method showed that the proposed method ensures several meters of positioning accuracy while ensuring processing speed as fast as the feature-based methods.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.11-17
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• 2022

In this paper, a model that can increase the efficiency of work in arranging interior furniture by applying augmented reality technology was studied. In the existing system to which augmented reality is currently applied, there is a problem in that information is limitedly provided depending on the size and nature of the company's product when outputting the image of furniture. To solve this problem, this paper presents an AR labeling algorithm. The AR labeling algorithm extracts feature points from the captured images and builds a database including indoor location information. A method of detecting and learning the location data of furniture in an indoor space was adopted using the CNN technique. Through the learned result, it is confirmed that the error between the indoor location and the location shown by learning can be significantly reduced. In addition, a study was conducted to allow users to easily place desired furniture through augmented reality by receiving detailed information about furniture along with accurate image extraction of furniture. As a result of the study, the accuracy and loss rate of the model were found to be 99% and 0.026, indicating the significance of this study by securing reliability. The results of this study are expected to satisfy consumers' satisfaction and purchase desires by accurately arranging desired furniture indoors through the design and implementation of AR labels.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.343-350
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• 2022

It is worth verifying the effectiveness of data integration between data with different features. This study investigated whether the data integration affects the accuracy of deep neural network (DNN), and which integration method shows the best improvement. This study used two different public datasets. One public dataset was taken in an actual farm in India. And another was taken in a laboratory environment in Korea. Leaf images were selected from two different public datasets to have five classes which includes normal and four different types of plant diseases. DNN used pre-trained VGG16 as a feature extractor and multi-layer perceptron as a classifier. Data were integrated into three different ways to be used for the training process. DNN was trained in a supervised manner via the integrated data. The trained DNN was evaluated by using a test dataset taken in an actual farm. DNN shows the best accuracy for the test dataset when DNN was first trained by images taken in the laboratory environment and then trained by images taken in the actual farm. The results show that data integration between plant images taken in a different environment helps improve the performance of deep neural networks. And the results also confirmed that independent use of plant images taken in different environments during the training process is more effective in improving the performance of DNN.

• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.303-311
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• 2019

is a film festival in conjunction with that shows about 50 works from 25 countries. It has become the only martial arts action film festival going on in Korea, with 32 feature films and 24 short films for a total of six days during the event from August 30 to September 6. has the slogan 'Muye, change the history of movies!' Through the movie, it sheds light on the value of life pursued by the martial arts spirit around Samjae, the core value of martial arts, and explores the aesthetic value of the most beautiful gesture that humans can make through the movement of martial arts centered on the space of dots, good and cotton. And through this film festival, I saw the potential to grow into a festival with the world. With this film festival, the identity of is established as a sustainable film festival, not as a single film festival, and image of martial arts action movies, which are part of genre movies, through the certainty of this image, differentiates itself from domestic and international film festivals, and does not stay in Northeast Asia or in Southeast Asia. Then, let's study the value of the future through the results of this film festival. In addition, we will study ways to increase the probability of growth as the best cultural and arts festival held along with the world's only international martial arts competition.

• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.938-943
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• 2003

In this paper, we Propose a method using the Tikhonov-Miller process to improve the robustness of watermarking under various attacks. A visually recognizable pattern watermark is embedded in the LH2, HL2 and HH2 subband of wavelet transformed domain using threshold and besides watermark is embeded by utilizing HVS(Human Visual System) feature. The pattern watermark was interlaced after random Permutation for a security and an extraction rate. To demonstrate the improvement of robustness and similarity of the proposed method, we applied some basic algorithm of image processing such as scaling, filtering, cropping, histogram equalizing and lossy compression(JPEG, gif). As a result of experiment, the proposed method was able to embed robust watermark invisibility and extract with an excellent normalized correlation of watermark under various attacks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.12C
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• pp.1239-1249
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• 2003

Gaze detection is to locate the position on a monitor screen where a user is looking by computer vision. Previous gaze detection system uses a wide view camera, which can capture the whole face of user. However, the image resolution is too low with such a camera and the fine movements of user's eye cannot be exactly detected. So, we implement the gaze detection system with a wide view camera and a narrow view camera. In order to detect the position of user's eye changed by facial movements, the narrow view camera has the functionalities of auto focusing and auto pan/tilt based on the detected 3D facial feature positions. As experimental results, we can obtain the facial and eye gaze position on a monitor and the gaze position accuracy between the computed positions and the real ones is about 3.1 cm of RMS error in case of Permitting facial movements and 3.57 cm in case of permitting facial and eye movement. The processing time is so short as to be implemented in real-time system(below 30 msec in Pentium -IV 1.8 GHz)

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.632-641
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• 2000

Conventional character extraction methods extract character regions using methods such as color reduction, region split and merge and texture analysis from the whole image. Because these methods use many heuristic variables and thresholding values derived from a priori knowledge, it is difficult to generalize them algorithmically. In this paper, we propose a method that can extract character regions using a topographical feature extraction method and a point-line-region extension method. The proposed method can also solve the problems of conventional methods by reducing heuristic variables and generalizing thresholding values. We see that character regions can be extracted by generalized variables and thresolding values without using a priori knowledge of character region. Experimental results show that the candidate region extraction rate is 100%, and the character region extraction rate is over 98%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.7
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• pp.4508-4515
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• 2014

Real-time body detection has been researched actively. On the other hand, the detection rate of color distorted images is low because most existing detection methods use static skin color model. Therefore, this paper proposes a new method for detecting the skin color region using a gradient map and saturation features. The basic procedure of the proposed method sequentially consists of creating a gradient map, extracting a gradient feature of skin regions, noise removal using the saturation features of skin, creating a cluster for extraction regions, detecting skin regions using cluster information, and verifying the results. This method uses features other than the color to strengthen skin detection not affected by light, race, age, individual features, etc. The results of the detection rate showed that the proposed method is 10% or more higher than the traditional methods.

• Journal of Korea Multimedia Society
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• v.16 no.8
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• pp.927-933
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• 2013

Face detection algorithm of OpenCV recognizes the faces by Haar matching between input image and Haar features which are learned through a set of training images consisting of many front faces. Therefore the face detection method by Haar matching yields a high face detection rate for the front faces but not in the case of the pan and deformed faces. On the assumption that distributional characteristics of color histogram is similar even if deformed or side faces, a face detection method using the histogram pattern matching is proposed in this paper. In the case of the missed detection and false detection caused by Haar matching, the proposed face detection algorithm applies the histogram pattern matching with the correct detected face area of the previous frame so that the face region with the most similar histogram distribution is determined. The experiment for evaluating the face detection performance reveals that the face detection rate was enhanced about 8% than the conventional method.

• Journal of the Korean Society of Costume
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• v.63 no.8
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• pp.43-57
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• 2013

The purpose of this research is to systemize the fashion digital storytelling by analyzing the communication method and its elements, and extracting the characteristics and processes of digital storytelling. Based on the previous study on the characteristics and types of storytelling the following things have been researched: 1) the process of digital storytelling in the communication process, 2) the concept and the feature of the academia of digital storytelling 3) storytelling in the document research. On the groundwork of the document research, we were able to sort out the various types, and formed a system of the features in the fashion digital storytelling cases, mainly in the four collections (Milan, Paris, London, New York) from 2000's to recent years of 2010. The types of fashion digital storytelling are episode type, narrative type, and creative type. The characteristics of each of the types are as follows. Firstly, the episode type communicates through the digital media based on the information or fact of the fashion designer brand. Secondly, narrative type communicates with the consumers using previous literature or an existing idea of the original cultural form that is rearranged in digital story expressed by the digital media. Lastly, creative type makes the designer's and consumer's susceptibility and creativity communicate through the newly made story, which expresses the unique originality of the designer. It seems that the cases and studies of using the fashion digital storytelling will increase because of its short history and lack of the case study. Fashion designer brands will show their brand image using the digital storytelling because they are able to better express originality, creativity and imagination of the fashion designer, which were factors that could not be conveyed through fashion alone.