• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11C
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• pp.1029-1039
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• 2009

In this paper, the existing disparity aquisition algorithms were analyzed, on the bases of which a disparity generation technique that is superior in accuracy to the generation time was proposed. Basically it uses a pixel-by-pixel motion estimation technique. It has a merit of possibility of a high-speed operation. But the motion estimation technique has a disadvantage of lower accuracy because it depends on the similarity of the matching window regardless of the distribution characteristics of the texture in an image. Therefore, an enhanced technique to increase the accuracy of the disparity is required. This paper introduced a variable-sized window matching technique for this requirement. By the proposed technique, high accuracies could be obtained at the homogeneous regions and the object edges. A hardware to generate disparity image was designed, which was optimized to the processing speed so that a high throughput is possible. The hardware was designed by Verilog-HDL and synthesized using Hynix $0.35{\mu}m$ CMOS cell library. The designed hardware was operated stably at 120MHz using Cadence NC-VerilogTM and could process 15 frames per second at this clock frequency.

• The KIPS Transactions:PartD
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• v.13D no.1 s.104
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• pp.29-36
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• 2006

In this paper, we present a leaf image retrieval system that represents and retrieves leaf images based on their shape. For more effective representation of leaf images, we improved an existing MPP algorithm. Also, in order to reduce the response time, we proposed a new dynamic matching algorithm at basically revises the Nearest Neighbor search. The system provides users with an interface for uploading query images or tools to generate queries based on shape features and retrieves images based on their similarity. For convenience, users are allowed to easily query images by sketching leaf shape or leaf arrangement on the web. In the experiment, we constructed an image database of Korean native plants and measured the system performance by counting the number of similar images retrieved for queries.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.356-359
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• 2000

In this paper, we propose a model based moving object tracking algorithm in dynamic scene. To adapt the shape change of the moving object, the Hausdorff distance is applied as the measurement of similarity between model and image. To reduce the processing time, 2-D logarithmic search method is applied for locate the position of moving object. Experiments on a running motorcycle, the result showed that the mean square error of real position and tracking result is 1.845 and consequently, matching process is relatively simple and reduced.

• ETRI Journal
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• v.44 no.1
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• pp.73-84
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• 2022

The moving picture experts group (MPEG) immersive video (MIV) technology has been actively developed and standardized to efficiently deliver immersive video to viewers in order for them to experience immersion and realism in various realistic and virtual environments. Such services are provided by MIV technology, which uses multiview videos as input. The pruning process, which is an important component of MIV technology, reduces interview redundancy in multiviews videos. The primary aim of the pruning process is to reduce the amount of data that available video codec must handle. In this study, two approaches are presented to improve the existing pruning algorithm. The first method determines the order in which images are pruned. The amount of overlapping region between the source views is then used to determine the pruning order. The second method considers global region-wise color similarity to minimize matching ambiguity when determining the pruning area. The proposed methods are evaluated under common test condition of MIV, and the results show that incorporating the proposed methods can improve both objective and subjective quality.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.2
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• pp.117-128
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• 2001

In order to achieve optimal retrieval, i.e., to find the best match to a query according to a certain similarity measure, the exhaustive search should be performed literally for all the images in a database. However, the straightforward exhaustive search algorithm is computationally expensive in large image databases. To reduce its heavy computational cost, this paper presents a fast exhaustive multi-resolution search algorithm based on image database clustering. Firstly, the proposed algorithm partitions the whole image data set into a pre-defined number of clusters having similar feature contents. Next, for a given query, it checks the lower bound of distances in each cluster, eliminating disqualified clusters. Then, it only examines the candidates in the remaining clusters. To alleviate unnecessary feature matching operations in the search procedure, the distance inequality property is employed based on a multi-resolution data structure. The proposed algorithm realizes a fast exhaustive multi-resolution search for either the best match or multiple best matches to the query. Using luminance histograms as a feature, we prove that the proposed algorithm guarantees optimal retrieval with high searching speed.

• The Transactions of the Korea Information Processing Society
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• v.5 no.7
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• pp.1923-1932
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• 1998

This paper deals with a 2-D objects recognition algorithm. And in this paper, we present an algorithm which can reduce the computation time in model retrieval by means of hashing technique instead of using the binary~tree method. In this paper, we treat an object boundary as a string of structural units and use an attributed string matching algorithm to compute similarity measure between two strings. We select from the privileged strings a privileged string wIth mmimal eccentricity. This privileged string is treated as the reference string. And thell we wllstructed hash table using the distance between privileged string and the reference string as a key value. Once the database of all model strings is built, the recognition proceeds by segmenting the scene into a polygonal approximation. The distance between privileged string extracted from the scene and the reference string is used for model hypothesis rerieval from the table. As a result of the computer simulation, the proposed method can recognize objects only computing, the distance 2-3tiems, while previous method should compute the distance 8-10 times for model retrieval.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.36-45
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• 2009

Recently, there are interested in the automatic traffic flowing and accident detection using various low level information from video in the road. In this paper, the automatic traffic flowing and algorithm, and application of traffic accident detection using traffic management systems are studied. To achieve these purposes, the spatio-temporal relation models using topological and directional relations have been made, then a matching of the proposed models with the directional motion verbs proposed by Levin's verbs of inherently directed motion is applied. Finally, the synonym and antonym are inserted by using WordNet. For the similarity measuring between proposed modeling and trajectory of moving object in the video, the objects are extracted, and then compared with the trajectories of moving objects by the proposed modeling. Because of the different features with each proposed modeling, the rules that have been generated will be applied to the similarity measurement by TSR (Tangent Space Representation). Through this research, we can extend our results to the automatic accident detection of vehicle using CCTV.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.141-150
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• 2011

Precise image-to-image registration is required to process multi-sensor data together. The purpose of this paper is to develop an algorithm that register between high-resolution optical and SAR images using linear features. As a pre-processing step, initial alignment was fulfilled using manually selected tie points to remove any dislocations caused by scale difference, rotation, and translation of images. Canny edge operator was applied to both images to extract linear features. These features were used to design a cost function that finds matching points based on their similarity. Outliers having larger geometric differences than general matching points were eliminated. The remaining points were used to construct a new transformation model, which was combined the piecewise linear function with the global affine transformation, and applied to increase the accuracy of geometric correction.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1243-1258
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• 2017

A new medical materials scheduling system and its modeling method for the complex rescue are presented. Different from other similar system, first both the BeiDou Satellite Communication System (BSCS) and the Special Fiber-optic Communication Network (SFCN) are used to collect the rescue requirements and the location information of disaster areas. Then all these messages will be displayed in a special medical software terminal. After that the bipartite graph models are utilized to compute the optimal scheduling of medical materials. Finally, all these results will be transmitted back by the BSCS and the SFCN again to implement a fast guidance of medical rescue. The sole drug scheduling issue, the multiple drugs scheduling issue, and the backup-scheme selection issue are all utilized: the Kuhn-Munkres algorithm is used to realize the optimal matching of sole drug scheduling issue, the spectral clustering-based method is employed to calculate the optimal distribution of multiple drugs scheduling issue, and the similarity metric of neighboring matrix is utilized to realize the estimation of backup-scheme selection issue of medical materials. Many simulation analysis experiments and applications have proved the correctness of proposed technique and system.

• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.95-105
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• 2005

As the security system using facial recognition, the recognition performance depends on the environments (e. g. face expression, hair style, age and make-up etc.) For the revision of easily changeable environment, it's generally used to set up the threshold, replace the face image which covers the threshold into images already registered, and update the face images additionally. However, this usage has the weakness of inaccuracy matching results or can easily active by analogous face images. So, we propose the genetic algorithm which absorbs greatly the facial similarity degree and the recognition target variety, and has excellence studying capacity to avoid registering inaccuracy. We experimented variable and similar face images (each 30 face images per one, total 300 images) and performed inherent face images based on ingredient analysis as face recognition technique. The proposed method resulted in not only the recognition improvement of a dominant gene but also decreasing the reaction rate to a recessive gene.