• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1350-1358
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• 1999

이 논문에서는 유전밴드 영상신호에 포함되어 있는 지형적 특징을 이용하여 밝기의 변화가 일정하지 않은 유전밴드를 인식하는 방법을 연구하였다. 유전밴드는 동일인을 식별하는데 있어서 지문보다 높은 신뢰성을 가지고 있으므로, 유전밴드 영상에서 유전밴드의 유무와 위치를 자동적으로 검출하는 것은 매우 중요하다. 레인내의 밝기의 변화가 일정한 유전밴드는 미분연산자에 의해 검출할 수 있지만, 밝기의 변화가 일정하지 않은 레인내의 유전밴드는 일반적인 인식방법에 의해서는 검출하기 어렵다. 따라서 유전밴드 영상으로부터 지형적 특징을 추출하고, 이것으로부터 계산한 곡률(curvature)의 크기에 의해 유전밴드를 인식함으로써 레인의 밝기가 변화하는 경우에도 효과적으로 인식하였다.Abstract This paper presents recognition of DNA band using the topographical features of DNA band images. The DNA band provides a more reliable way of identification than fingerprints. Recognition based on differentiation operators can easily detect the DNA band if the brightness of lane in the image is almost uniform. When the brightness of the lane changes gradually, the DNA bands are hard to be recognized. Using the curvature magnitude of the lane computed from topographic features extracted from DNA images, the DNA bands are efficiently recognized in the lane whose brightness changes.

• Journal of Navigation and Port Research
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• v.42 no.3
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• pp.237-244
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• 2018

When underwater rubble leveling work is carried out by a robot, real-time information on the topography around the robot is required for remote control. If the topographical information with respect to the current position of the robot is displayed as a 3D graphic image, it allows the operator to plan the working schedules and to avoid accidents like rollovers. Up until now, the topographical recognition was conducted by multi-beam sonars, which were only used to assess the quality before and after the work and could not be used to provide real-time information for remote control. This research measures the force delivered to the bucket which presses the mound to determine whether contact is made or not, and the contact position is calculated by reading the cylinder length. A variable bang-bang control algorithm is applied to control the heavy robot arms for the positioning of the bucket. The proposed method allows operators to easily recognize the terrain and intuitively plan the working schedules by showing relatively 3-D gratifications with respect to the robot body. In addition, the operating patterns of a skilled operator are programmed for raking, pushing, moving, and measuring so that they are automatically applied to the underwater rubble leveling work of the robot.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.154-160
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• 1995

Maps are one of the most complicated types of drawings. Drawing recognition technology is not yet sophisticated enough for automated map reading. To automatically extract a road map directly form more complicated topographical maps, a very complicated algorithm is needed, simce the image generally involves such complicated patterns as symbols, characters, residential sections, rivers,etc. This paper describes a new feature extraction method based on the human optical neural field. We apply this method to extract complete set of road segments from topographical maps. The proposed method successfully extract road segments from various areas.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.11
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• pp.1496-1505
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• 1995

Maps are one of the most complicated types of drawings. Drawing recognition technology is not yet sophisticated enough for automated map reading. To automatically extract a road map dircetly from complicated topographical maps, a very sophisticated algorithm is needed, since the image generally involvfes such complicated patterns as symbols, characters, residential sections, rivers, railroads, etc. This paper proposes a new feature extraction method based on the morphology. We apply this method to extract complete set of road segments from topographical maps. The proposed method successfully extract road segments from various areas.

• The Journal of the Acoustical Society of Korea
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• v.14 no.2
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• pp.101-112
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• 1995

In order to construct a feature map-based phoneme classification system for speech recognition, two procedures are usually required. One is clustering and the other is labeling. In this paper, we present a phoneme classification system based on the Kohonen's Self-Organizing Feature Map (SOFM) for clusterer and labeler. It is known that the SOFM performs self-organizing process by which optimal local topographical mapping of the signal space and yields a reasonably high accuracy in recognition tasks. Consequently, SOFM can effectively be applied to the recognition of phonemes. Besides to improve the performance of the phoneme classification system, we propose the learning algorithm combined with the classical K-mans clustering algorithm in fine-tuning stage. In order to evaluate the performance of the proposed phoneme classification algorithm, we first use totaly 43 phonemes which construct six intra-class feature maps for six different phoneme classes. From the speaker-dependent phoneme classification tests using these six feature maps, we obtain recognition rate of $87.2\%$ and confirm that the proposed algorithm is an efficient method for improvement of recognition performance and convergence speed.

• The Transactions of the Korea Information Processing Society
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• v.1 no.4
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• pp.452-460
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• 1994

Maps are one of the most complicated types of drawings. Drawing recognition technology is not yet sophisticated enough for automated map reading To automatically extract a road map directly from more complicated topographical maps, a very complicated algorithm is needed, since the image generally involves such complicated patterns as symbols, characters, residential sections, rivers, railroads, etc. This paper describes a new feature extraction method based on the human optical neural field. We apply this method to extract complete set of road segments from topographical maps. The proposed method successfully extract road segments from various areas.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.3
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• pp.16-24
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• 2019

Recently, research on emotion recognition based on EEG has attracted great interest from human-robot interaction field. In this paper, we propose a method of labeling using image-based EEG topography instead of evaluating emotions through self-assessment and annotation labeling methods used in MAHNOB HCI. The proposed method evaluates the emotion by machine learning model that learned EEG signal transformed into topographical image. In the experiments using MAHNOB-HCI database, we compared the performance of training EEG topography labeling models of SVM and kNN. The accuracy of the proposed method was 54.2% in SVM and 57.7% in kNN.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2355-2362
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• 2016

Seg fog removal is an important issue concerned by both computer vision and image processing. Sea fog or haze removal is widely used in lots of fields, such as automatic control system, CCTV, and image recognition. Color image dehazing techniques have been extensively studied, and expecially the dark channel prior(DCP) technique has been widely used. This paper propose a fast and efficient image prior - dark channel prior to remove seg-fog from a single digital image based on the GPU. We implement the basic parallel program and then optimize it to obtain performance acceleration with more than 250 times. While paralleling and the optimizing the algorithm, we improve some parts of the original serial program or basic parallel program according to the characteristics of several steps. The proposed GPU programming algorithm and implementation results may be used with advantages as pre-processing in many systems, such as safe navigation for ship, topographical survey, intelligent vehicles, etc.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.3
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• pp.49-61
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• 2019

This study aims to examine the spatial recognition of the characters who visited Anuisamdong(安義三洞) in the past and left it in the literature. Thus, the school's relationship between people identified in the relevant literature was analyzed and the elements of landscape were extracted. The results were as follows; First, The figures who authored the literature on Anuisamdong were related to scholars living in Anuihyun(安義縣), along with the Yeongnam confucian genealogy. Starting with Jung, Yeo-Chang(鄭汝昌) in the 15th century, a relationship centered on Nammyeong School(南溟學派) in the 16th century was formed. At that time, people had toured the Anuisamdong regardless of the academic background. In the 17th century, Nammyeong School were in conflict with Toegye School(退溪學派), so Toegye School's influence had no record. In the 18th century, the proportion of Nammyeong School, Toegye School, and Kiho School(畿湖學派) appeared similar as they evolved into the Yeongnam School(嶺南學派). After the 19th century, the proportion of patriots who participated in the anti-Japanese movement was higher than that of schools. Second, The main places used in the literature related to Anuisamdongwere the order of Wonhakdong(猿鶴洞), Hwrimdong(花林洞) and Simjindong(尋眞洞). There are a total of 21 major elements used for the related literature, of which Suseungdae Rock(搜勝臺), Morijae House(某里齋), Nongwaljeong Pavilion(弄月亭), Sasundae Rock(四仙臺) and Cheoksuam Rock(滌愁巖) were the main subjects. Elements of Wonhakdong have been in the spotlight since the 16th century, focusing on Suseungdae Rock. Although the elements of Hwarimdong have been increasing gradually since the 18th century, the ratio of Simjindong to Wonhakdong and Hwarimdong was relatively small. Third, The relationship between the figures who visited the Anuisamdong and the spatial recognition of the Anuisamdong was divided into landscape awareness, emotional awareness and symbolic recognition. The Anuisamdong's scenic view is mostly identified by its description of the waterscape and topographical landscape, which people may have perceived as a scenic site centered on the valley view at the time. The mutual influence of Nammyeong School and Toegye School in the 16th and 17th centuries led to a scene in which the major figures of each school recognized pleasure as a culture of training, and a feeling of longing for the traces of past ancestors as the 18th century travel culture and the 19th century chaotic situation. In addition, the symbolic expression that usually appears is likely to have been recognized as a unworldly place, as the location of the immortal world is confirmed.