• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.4
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• pp.370-380
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• 2002

This paper proposes an ATR (Automatic Target Recognition) algorithm for identifying non-occluded and occluded military vehicles in natural FLIR (Forward Looking InfraRed) images. After segmenting a target, a radial function is defined from the target boundary to extract global shape features. Also, to extract local shape features of upper region of a target, a distance function is defined from boundary points and a line between two extreme points. From two functions and target contour, four global and four local shape features are proposed. They are much more invariant to translation, rotation and scale transform than traditional feature sets. In the experiments, we show that the proposed feature set is superior to the traditional feature sets with respect to the similarity-transform invariance and recognition performance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.5
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• pp.303-311
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• 2003

Since the MPEG-4 visual standard enables content-based functionalities, it is necessary to extract video object from natural video sequences. Segmentation algorithms can largely be classified into automatic segmentation and user-assisted segmentation. In this paper, we propose a user-assisted VOP generation method based on the geometric active contour. Since the geometric active contour, unlike the parametric active contour, employs the level set method to evolve the curve, we can draw the initial curve independent of the shape of the object. In order to generate the edge function from a smoothed image, we propose a vector-valued diffusion process in the LUV color space. We also present a discrete 3-D diffusion model for easy implementation. By combining the curve shrinkage in the vector field space with the curve expansion in the empty vector space, we can make accurate extraction of visual objects from video sequences.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.25-31
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• 2017

This paper aims to develope the technology for monitoring and identifying webtoon works that are being illegally distributed through the web-hard, torrent and overseas websites. The technology is to effectively prevent the illegal distribution and protect the copyrights of the webtoon works, leading to create a healthy market. This paper deals with the technology for (a) automatic collection of webtoon works from the webtoon service sites, (b) extraction of the features from the images of the collected webtoon works, and (c) registers them in the feature database. For these purposes, the required system performance and features were analyzed and the structures of webtoon service sites were examined, through which the system for automatic registration of webtoon works and features was developed. The system can work for the early stage blockage of illegal distributions of webtoon works which occur during the period from webtoon posting to feature registration.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.4
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• pp.1-10
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• 2000

Satellite remote sensing images have much more information compared to a paper map. But these images are generally handled as particular image format gained from optical sensor, and must be processed and analyzed by computer with high priced digital image processing system. For the extraction of digital elevation model(DEM) from satellite image, we used the overlay image by SPOT-3 of Chuncheon area at the Kangwon province. According to the image condition, the precious geometric correction, the bundle adjustment for ortho-image generation and the stereo image mapping by several technical approaches were processed. So that we developed the methods of automatic DEM extraction and efficient stereo image map generation which can improve the digital image processing steps. Also, we applied the multiple direction birdeye view image for modeling and analysis using the remotely sensed overlay images with high resolution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.634-640
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• 2018

In this paper, we propose an automatic extraction algorithm of region of interest(ROI) based on medical x-ray images. The proposed algorithm uses segmentation, feature extraction, and reference image matching to detect lesion sites in the input image. The extracted region is searched for matching lesion images in the reference DB, and the matched results are automatically extracted using the Kalman filter based fitness feedback. The proposed algorithm is extracts the contour of the left hand image for extract growth plate based on the left x-ray input image. It creates a candidate region using multi scale Hessian-matrix based sessionization. As a result, the proposed algorithm was able to split rapidly in 0.02 seconds during the ROI segmentation phase, also when extracting ROI based on segmented image 0.53, the reinforcement phase was able to perform very accurate image segmentation in 0.49 seconds.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2121-2128
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• 2015

In this paper presents a method of extracting reliable and regions of interest (ROI) in barcode for the purpose of factory automation. backgrounds are separated based on directional components and the characteristics of detected patterns. post-processing is performed on candidate images with analysis of problems caused by blur, rotation and areas of high similarity. In addition, the resizing factor is used to achieve faster calculations through image resizing. The input images contained multiple product or barcode for application to diverse automation environments; a high extraction success rate is accomplished despite the maximum shooting distance of 80 cm. Simulations involving images with various shooting distances gave an ROI detection rate of 100% and a post-processing success rate of 99.3%.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.65-79
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• 2003

In general, the extraction and recognition of identifier is very hard work, because the scale or location of identifier is not fixed-form. And, because the provided image is contained by camera, it has some noises. In this paper, we propose methods for automatic detecting edge using canny edge mask. After detecting edges, we extract regions of identifier by detected edge information's. In regions of identifier, we extract each identifier using contour tracking algorithm. The self-generation supervised learning algorithm is proposed for recognizing them, which has the algorithm of combining the enhanced ART1 and the supervised teaming method. The proposed method has applied to the container images. The extraction rate of identifier obtained by using contour tracking algorithm showed better results than that from the histogram method. Furthermore, the recognition rate of the self-generation supervised teaming method based on enhanced ART1 was improved much more than that of the self-generation supervised learning method based conventional ART1.

• Journal of the Korean Society for information Management
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• v.25 no.1
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• pp.19-41
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• 2008

Cue words and phrases of critical sentences, Paradigms knowing the critical information between sentences, Rules extracting the sentences contained critical information and producing the critical sentences were made to construct the critical abstract of scholar journals in the web environment. The ontology aided to accomplish above works were designed, to manage and operate the cue words and phrases in documents and the symptoms related to Purpose, Method, Result, and Conclusion sentences. The results of performance test remarked to improve the advancement of extraction and production rules and the reinforcement of ontology's relationship.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.517-517
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• 2002

Recently in the field of telecommunication, there is much interest in geo-surface characteristics of urban areas. Geophysical properties of urban features are now incorporated with accurate positional information to model the telecommunication environment. In this study, three-dimensional buildings are geometrically reconstructed from existing vector maps and aerial images. Accurate digital vector maps are easily available in Korea. However existing maps, which had been produced for GIS applications, do not have height information which is critical to three dimensional building reconstruction. Image matching techniques were applied to aerial image stereopairs to automatically extract the height information of buildings. Planimetric coordinates from vector maps were used as initial guides in the process. Future studies will be undertaken to link geophysical properties to the three-dimensional spatial objects reconstructed from this study thus bringing the telecommunication environment model closer to reality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.6000-6017
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• 2018

This paper presents a new descriptor, named Histograms of Prominent Edge Directions (HPED), for the recognition of facial expressions in a person-independent environment. In this paper, we raise the issue of sampling error in generating the code-histogram from spatial regions of the face image, as observed in the existing descriptors. HPED describes facial appearance changes based on the statistical distribution of the top two prominent edge directions (i.e., primary and secondary direction) captured over small spatial regions of the face. Compared to existing descriptors, HPED uses a smaller number of code-bins to describe the spatial regions, which helps avoid sampling error despite having fewer samples while preserving the valuable spatial information. In contrast to the existing Histogram of Oriented Gradients (HOG) that uses the histogram of the primary edge direction (i.e., gradient orientation) only, we additionally consider the histogram of the secondary edge direction, which provides more meaningful shape information related to the local texture. Experiments on popular facial expression datasets demonstrate the superior performance of the proposed HPED against existing descriptors in a person-independent environment.