• KIPS Transactions on Software and Data Engineering
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• v.11 no.2
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• pp.87-92
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• 2022

Image-based application testing proposes an application testing method via image structure comparison. This test method allows testing on various devices without relying on various types of device operating systems or GUI. Traditional studies required the creation of a tester for each variant in the existing case, because it differs from the correct image for operating system changes, screen animation execution, and resolution changes. The study determined that the screen is the same for variations. The tester compares the underlying structure of the objects in the two images and extracts the regions in which the differences exist in the images, and compares image similarity as characteristic points of the Faster D2-Net. The development of the Faster D2-Net reduced the number of operations and spatial losses compared to the D2-Net, making it suitable for extracting features from application images and reducing test performance time.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.79-84
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• 2019

Video image based technology is being used in various fields with continuous development. The demand for vision system technology that analyzes and discriminates image objects acquired through cameras is rapidly increasing. Image processing is one of the core technologies of vision systems, and is used for defect inspection in the semiconductor manufacturing field, object recognition inspection such as the number of tire surfaces and symbols. In addition, research into license plate recognition is ongoing, and it is necessary to recognize objects quickly and accurately. In this paper, propose a recognition model through the rotational alignment of objects after checking the angle value of the tilt of the object in the input video image for the recognition of inclined objects such as numbers or symbols marked on the surface. The proposed model can perform object recognition of the rotationally sorted image after extracting the object region and calculating the angle of the object based on the contour algorithm. The proposed model extracts the object region based on the contour algorithm, calculates the angle of the object, and then performs object recognition on the rotationally aligned image. In future research, it is necessary to study template matching through machine learning.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.250-251
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• 2010

디지털 카메라의 보급으로 이미지처리 분야에서 정지영상을 이용한 다양한 기술 개발이 화두가 되고 있다. 스테레오 영상은 정지영상보다 소비자의 시각적 욕구를 충족시킬 수 있는 영상을 표현하기 때문에 스테레오 영상기술에 대한 관심이 높아지고 있다. 본 논문에서는 하나의 카메라로 같은 객체를 다른 위치에서 찍은 2장의 정지영상을 통해 스테레오 영상을 제작하는 방법을 제안한다. 실험 영상으로 디지털카메라로 찍은 좌측 영상과 우측영상을 사용한다. 두 영상의 제어점이 될 코너를 검출한 후, 유클리드의 좌표로 바꿔준다. 이 좌표들을 통해 각 제어점에 인접해 있는 좌표 4개를 추출한다. 이 인접 좌표들이 우측 정지 영상의 인접 좌표에 매칭 되는 횟수를 계산하여, 가장 많은 매칭 좌표를 갖는 스케일 요소로 좌측 정지영상을 회전과 이동시켜 목적 영상인 우측 영상에 매칭시킴으로써 스테레오 영상을 구현한다.

• Annual Conference of KIPS
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• 2002.11a
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• pp.57-60
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• 2002

본 논문에서는 능동윤곽모델(active contour model)의 잘 알려져 있는 스네이크(snake) 알고리즘을 스테레오영상에 적용하여 좌 우 영상의 disparity 정보를 이용 객체의 경계선을 찾는 알고리즘을 제안한다. 스네이크는 객체의 경계를 얻기 위해 에지정보를 사용하는데 실제 이미지에서 객체의 경계가 아닌 인접한 주위의 강한 애지(edge)에 대해서도 영향을 받게 되는 문제가 있다. 이러한 문제를 해결하기 위해 스테레오영상의 disparity 정보를 이용하여 이를 개선하고 disparity 측정에 사용되는 블록매칭(block matching)방법을 스네이크 알고리즘에 적용시켰다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.183-189
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• 2009

Recently, PCS, PDA and mobile devices, such as the proliferation of spread, GPS (Global Positioning System) the use of, the rapid development of wireless network and a regular user even images, audio, video, multimedia data, such as increased use is for. In particular, video data among multimedia data, unlike the moving object, text or image data that contains information about the movements and changes in the space of time, depending on the kinds of changes that have sigongganjeok attributes. Spatial location of objects on the flow of time, changing according to the moving object (Moving Object) of the continuous movement trajectory of the meeting is called, from the user from the database that contains a given query trajectory and data trajectory similar to the finding of similar trajectory Search (Similar Sub-trajectory Retrieval) is called. To search for the trajectory, and these variations, and given the similar trajectory of the user query (Tolerance) in the search for a similar trajectory to approximate data matching (Approximate Matching) should be available. In addition, a large multimedia data from the database that you only want to be able to find a faster time-effective ways to search different from the existing research is required. To this end, in this paper effectively divided into a grid to search for the trajectory to the trajectory of moving objects, similar to the effective support of the search trajectory offers a new grid-based search techniques.

• Convergence Security Journal
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• v.22 no.1
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• pp.29-38
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• 2022

The importance of prevention of epidemics is increasing due to the serious spread of infectious diseases. For prevention of epidemics, we need to focus on the non-contact industry. Therefore, in this paper, a face recognition door lock that controls access through non-contact is designed and developed. First very simple features are combined to find objects and face recognition is performed using Haar-based cascade algorithm. Then the texture of the image is binarized to find features using LBPH. An non-contact door lock system which composed of Raspberry PI 3B+ board, an ultrasonic sensor, a camera module, a motor, etc. are suggested. To verify actual performance and ascertain the impact of light sources, various experiment were conducted. As experimental results, the maximum value of the recognition rate was about 85.7%.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.507-512
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• 2001

Feature-based similarity has become an important research issue in multimedia database systems. The features of multimedia data are useful for discriminating between multimedia objects. the performance of conventional multidimensional data structures tends to deteriorate as the number of dimensions of feature vectors increase. The $R^{*}-Tree$ is the most successful variant of the R-Tree. In this paper, we propose a SOM-based $R^{*}-Tree$ as a new indexing method for high-dimensional feature vectors. The SOM-based $R^{*}-Tree$ combines SOM and $R^{*}-Tree$ to achieve search performance more scalable to high-dimensionalties. Self-Organizingf Maps (SOMs) provide mapping from high-dimensional feature vectors onto a two-dimensional space. The map is called a topological feature map, and preserves the mutual relationships (similarity) in the feature spaces of input data, clustering mutually similar feature vectors in neighboring nodes. Each node of the topological feature map holds a codebook vector. We experimentally compare the retrieval time cost of a SOM-based $R^{*}-Tree$ with of an SOM and $R^{*}-Tree$ using color feature vectors extracted from 40,000 images. The results show that the SOM-based $R^{*}-Tree$ outperform both the SOM and $R^{*}-Tree$ due to reduction of the number of nodes to build $R^{*}-Tree$ and retrieval time cost.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.57-74
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• 2022

Recently, artificial intelligence parking control systems have increased the recognition rate of vehicle license plates using deep learning, but there is a problem that they cannot determine vehicles with fake license plates. Despite these security problems, several institutions have been using the existing system so far. For example, in an experiment using a counterfeit license plate, there are cases of successful entry into major government agencies. This paper proposes an improved system over the existing artificial intelligence parking control system to prevent vehicles with such fake license plates from entering. The proposed method is to use the degree of matching of the front feature points of the vehicle as a passing criterion using the ORB algorithm that extracts information on feature points characterized by an image, just as the existing system uses the matching of vehicle license plates as a passing criterion. In addition, a procedure for checking whether a vehicle exists inside was included in the proposed system to prevent the entry of the same type of vehicle with a fake license plate. As a result of the experiment, it showed the improved performance in identifying vehicles with fake license plates compared to the existing system. These results confirmed that the methods proposed in this paper could be applied to the existing parking control system while taking the flow of the original artificial intelligence parking control system to prevent vehicles with fake license plates from entering.