• 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.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.749-752
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• 1998

Recognizing a human part becomes very important for applications which are based on the interaction between computers and their users. In this paper, we design and implement a system which recognizes and tracks a human head using a sequence of images. Difference images are used to easily extract feature vectors from images with very complex backgrounds. A human bhead is represented with an ellipse and recognized by searching for a maximum value from preprocessed gradient images. The method is developed by considering the fact that the tracking system should be real-time. The designed system not only shows an excellent performance for the normal up-right position of the head, but also for the cases of 360.deg. rotated head position, occluded images of heads, and tilted head positions.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.7
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• pp.821-826
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• 1999

This paper proposes a face recognition method using feature spaces and image vectors in the image plane. We obtain the 2-D feature space using the self-organizing map which has two inputs from the axis of the given image. The image vector consists of its weights and the average gray levels in the feature space. Also, we can reconstruct an normalized face by using the image vector having no connection with the size of the given face image. In the proposed method, each face is recognized with the best match of the feature spaces and the maximum match of the normally retrieval face images, respectively. For enhancing recognition rates, our method combines the two recognition methods by the feature spaces and the retrieval images. Simulations are conducted on the ORL(Olivetti Research laboratory) images of 40 persons, in which each person has 10 facial images, and the result shows 100% recognition and 14.5% rejection rates for the 20$\times$20 feature sizes and the 24$\times$28 retrieval image size.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.56-63
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• 2024

Despite the rapid strides in content-based image retrieval, a notable disparity persists between the visual features of images and the semantic features discerned by humans. Hence, image retrieval based on the association of semantic similarities recognized by humans with visual similarities is a difficult task for most image-retrieval systems. Our study endeavors to bridge this gap by refining image semantics, aligning them more closely with human perception. Deep learning techniques are used to semantically classify images and retrieve those that are semantically similar to personalized images. Moreover, we introduce a keyword-based image retrieval, enabling automatic labeling of images in mobile environments. The proposed approach can improve the performance of a mobile device with limited resources and bandwidth by performing retrieval based on the visual features and keywords of the image on the mobile device.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.1-5
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• 2003

In this paper, we realized a system that converts the character images of the printed Korean alphabet (Hangul) to the editable text documents by using the black and white CCD camera, We were able to abstract the contours information of the character which is based on the structural character by using the boundary tracing technique that is strong to the noise on the character recognition. By using the contours information, we recognized the horizontal vowels and vertical vowels of the character image and classify the character into the six patterns. After that, the character is divided to the unit of the consonant and vowel. The vowels are recognized by using the maximum length projection. The separated consonants are recognized by comparing the inputted pattern with the standard pattern that has the phase information of the boundary line change. We realized a system that the recognized characters are inputted to the word editor with the editable KS Hangul completion type code.

• Journal of the Korean Society of Costume
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• v.56 no.7 s.107
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• pp.18-32
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• 2006

The objectives of this research were to identify the differences of image evaluations by perceiver's gender, majors and jeans' finishing and to examine image characteristics that have an influence on attractiveness and preferences of jeans' finishing. The subjects are 96 undergraduate students in Los Angeles of the USA. Elegant and refined images had a significant effort on perceiver's gender, so men tended to highly evaluate jeans as elegant and refined images than did women. Soft images were recognized differently by perceiver's major, so non-specialists in design tended to highly evaluate jeans as soft images than did specialists in design. In finishing, shattered wash was evaluated as the most individual, attractive, energetic, and splendid images, and stone wash was evaluated as the most ordinary, unattractive, and plain images. Light images tended to have interaction effects by majors and finishing. Specialists in design did not perceive differences between light images from finishing well, but non-specialists in design perceived that stone wash finishing's image is lighter than indigo blue finishing's image. Sociable images had interaction effects by perceiver's gender, majors and jeans' finishing, and especially non-specialists in men estimated that shattered wash has the lowest sociable images in finishing. According to evaluations about finishing images of ladies' jeans, men tended to be attracted by splendid images, and women tended to be attracted by sexy images. In addition, both men and women were commonly attracted by feminine images, so the study found that feminine images is important image for developing jeans for ladies. According to evaluations about finishing images of ladies' jeans, men preferred sexy and natural images to comfortable and energetic images, and women preferred sexy and neat images. Female undergraduate students of the USA tended to be attracted by sexy images, and we found that actually they consider buying jeans with such images.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2005.05a
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• pp.110-115
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• 2005

Show window display is a technique of arranging goods for sales promotion, namely, motivating and inducing customers to purchase products. It is not simply exhibiting articles but a technical expression of values retained in exhibited articles and an integrated visual art comprehending color, lighting effect, the customers' angle of vision, differentiation from neighboring stores, harmony with properties, assistive roles of relevant goods, and entire messages provided by these elements. Show window display plays the role of a medium that expresses brand images and attracts consumers. Through the medium, the company's brand image is recognized and the recognition determines the trend of brand sales. Brand images planted to consumers seldom change, and wrong recognition affects not only the brand image but also the company image. The present study purposed to suggest show window display employing brand images different from traditional show window display, to examine the effects of brand images on consumers' intention to purchase, and to propose display design.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.22 no.1
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• pp.29-37
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• 1992

The temporomandibular joint was evaluated using magnetic resonance imaging using a urface coil in 11 patients having reciprocal clicking or locking and compared with the normal joint in five subjects. Serial multisection 3㎜-thick parasagittal, paracoronal, and axial image on both closing and opening mouth were obtained with a 1.5 Tesla MR system and surface coil using CSMEMP, GRASS, MPGR, powerful extensions of fast imaging that is currently under clinical evaluation. MR images obtained were analized correlating with the theory of internal derangement. The obtained results were as follows: 1. The serial findings of structures in joint were determined on the serially sectioned images of joint with reciprocal clicking or locking by CSMEMP and MPGR on closing mouth. 2. The delta shaped white images of synovial fluid in the glenoid fossa and on the posterior surface of condyle were revealed on the parasagittal images by MPGR on opening mouth as in the normal joints. 3. The white image of joint fluid surrounding meniscus was recognized on the paracoronal image by GRASS on opening mouth as in the normal joints. 4. In joints having temporomandibular dysfunction the smooth image of displaced meniscus was recognized, but otherwise in the normal joints the image of muscle was noted on the paracoronal image sectioned at the anterior portion of condyle by GRASS. 5. The more thickened fascial plane between superior and inferior belly of lateral pterygoid muscle was not recognizable in joints having temporomandibular dysfunction than in the normal joints.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.220-228
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• 2022

Image always carry useful information, detecting a text from scene images is imperative. The proposed work's purpose is to recognize scene text image, example boarding image kept on highways. Scene text detection on highways boarding's plays a vital role in road safety measures. At initial stage applying preprocessing techniques to the image is to sharpen and improve the features exist in the image. Likely, morphological operator were applied on images to remove the close gaps exists between objects. Here we proposed a two phase algorithm for extracting and recognizing text from scene images. In phase I text from scenery image is extracted by applying various image preprocessing techniques like blurring, erosion, tophat followed by applying thresholding, morphological gradient and by fixing kernel sizes, then canny edge detector is applied to detect the text contained in the scene images. In phase II text from scenery image recognized using MSER (Maximally Stable Extremal Region) and OCR; Proposed work aimed to detect the text contained in the scenery images from popular dataset repositories SVT, ICDAR 2003, MSRA-TD 500; these images were captured at various illumination and angles. Proposed algorithm produces higher accuracy in minimal execution time compared with state-of-the-art methodologies.

• Journal of Korea Multimedia Society
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• v.24 no.12
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• pp.1641-1652
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• 2021

To analyze the crime scene, the role of digital evidence such as CCTV and black box is very important. Such digital evidence is often damaged due to device defects or intentional deletion. In this case, the deleted video can be restored by well-known techniques like the frame-based recovery method. Especially, the data such as the video can be generally fragmented and saved in the case of the memory used almost fully. If the fragmented video were recovered in units of images, the sequence of the recovered images may not be continuous. In this paper, we proposed a new video restoration method to match the sequence of recovered images. First, the images are recovered through a frame-based recovery technique. Then, after analyzing the time information marked on the images, the time information was extracted and recognized via optical character recognition (OCR). Finally, the recovered images are rearranged based on the time information obtained by OCR. For performance evaluation, we evaluate the recovery rate of our proposed video restoration method. As a result, it was shown that the recovery rate for the fragmented video was recovered from a minimum of about 47% to a maximum of 98%.