• 통합자연과학논문집
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• 제2권3호
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• pp.202-206
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• 2009

Optical images based on the porous silicon exhibiting photoluminescence have been prepared from an electrochemical etching of n-type silicon wafer (boron-doped,<100> orientation, resistivity $1{\sim}10{\Omega}-cm$) by using a beam projector. The images remained in the substrate displayed an optical images correlating to the optical pattern and could be useful for optical data storage. This provides the ability to fabricate complex optical encoding in the surface of silicon.

• 한국멀티미디어학회논문지
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• 제9권2호
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• pp.160-171
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• 2006

본 논문에서는 복잡한 배경, 심한 조명 변화 등의 다양한 환경 변화에서도 얼굴을 정확히 검출하기 위하여 영역 분할을 이용한 얼굴 검출을 제안한다. 입력된 영상에서 배경요소들로, 인한 검출 오류를 줄이기 위하여 JSEG 방법을 사용하여 영상을 영역 단위로 분할한다. 분할된 각 영역에서 사전 정의된 피부색에 해당되는 픽셀들을 추출한다. 각 영역에서 추출된 픽셀들의 비율을 이용하여 얼굴 후보 영역을 결정한다. 그리고 결정된 얼굴 후보 영역에서 얼굴요소에 해당되는 눈과 눈썹이 위치 정보와 색상 정보를 이용하여 최종 얼굴 영역을 검출한다. 본 논문에서 제안한 방법을 이용하여 다양한 제약 조건을 지닌 영상들에 대하여 얼굴을 검출해본 결과, 배경이 복잡한 영상, 조명 변화가 심한 영상, 얼굴 크기가 다양한 영상, 얼굴이 다수 존재하는 영상들에서 좋은 검출 결과를 보여주었다.

• 대한전자공학회논문지SP
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• 제41권6호
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• pp.175-186
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• 2004

본 논문은 복잡한 컬러 영상에서의 문자 추출을 위한 텍스춰와 연결성분 방법의 결합된 방법을 제안한다. 자동 학습 방법으로 구축된 다층 신경망(multilayer perceptron)은 부트스트랩 학습 방법을 사용함으로써 별도의 특징값 추출 단계 없이 다양한 환경의 입력 영상에 대한 검출률(recall rate)을 향상시키며, 검출률을 향상함으로써 발생되는 정확도(precision rate) 저하 문제는, NMF(Non-negative matrix factorization)를 이용한 연결 성분 방법을 사용함으로써 극복한다. 문자의 존재 비율이 낮은 입력영상에 대하여 CAMShift 알고리즘을 이용한 영역 마킹 방법을 사용함으로써, 두 방법을 결합함으로써 야기되는 속도 저하 문제의 해결을 시도하였다. 이와 같이 텍스춰와 연결성분 방법을 결합함으로써 강건하고 효율적인 시스템을 구성할 수 있었다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2007년도 추계종합학술대회
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• pp.431-433
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• 2007

본 논문에서는 복잡한 영상, 특히 컨테이너 식별자가 속해 있는 영상에서의 문자영역을 추출하기 위하여 top-hat morphology 기법을 통해 획득된 텍스쳐 정보를 가로 및 세로 가중치를 가지는 클러스터링 기법을 이용하여 추출하는 방법을 제안한다. 실험을 통해 제안한 방법의 성능을 검증하고, 기존에 알려진 텍스쳐와 히스토그램을 이용하는 방법 등과 비교하여 그 성능이 향상됨을 확인한다.

• 한국광학회:학술대회논문집
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• 한국광학회 2003년도 하계학술발표회
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• pp.80-81
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• 2003

The psychophysical experiments were carried out by a panel of eleven observers on the image difference pairs displayed on the LCD (liquid crystal display)to quantify the quality changes of complex images imparted by the typical image processing operations. There were six different kinds of pairs according to their original image. The three types of visual tests performed were： pair-to-pair comparison of image differences for ordering the differences between images introduced by single or combination of image lightness change, contrast change, blurring, and sharpening, perceptibility and acceptability tests using ascending or descending series of image difference pairs ordered according to the size of their visual differences. (omitted)

• Journal of Information Processing Systems
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• 제17권6호
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• pp.1170-1178
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• 2021

This paper proposed a versatile algorithm based on a dual-tree complex wavelet transform for intensifying the visual aspect of medical images. First, the decomposition of the input image into a high sub-band and low-sub-band image is done. Further, to improve the resolution of the resulting image, the high sub-band image is interpolated using Lanczos interpolation. Also, contrast enhancement is performed by singular value decomposition (SVD). Finally, the image reconstruction is achieved by using an inverse wavelet transform. Then, the Gaussian filter will improve the visual quality of the image. We have collected images from the hospital and the internet for quantitative and qualitative analysis. These images act as a reference image for comparing the effectiveness of the proposed algorithm with the existing state-of-the-art. We have divided the proposed algorithm into several stages: preprocessing, contrast enhancement, resolution enhancement, and visual quality enhancement. Both analyses show the proposed algorithm's effectiveness compared to existing methods.

• 디지털융복합연구
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• 제15권4호
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• pp.267-273
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• 2017

각종 디지털 기기와 통신 기술의 발전으로 다양한 멀티미디어 콘텐츠의 생산과 유통이 폭발적으로 증가하고 있다. 이미지와 동영상 등의 멀티미디어 데이터의 검색을 위해서는 기존의 문자 위주의 검색과는 다른 접근 방식이 필요하다. 이미지의 여러 가지 물리적인 특징들을 정량화 하여 분석하고 이를 비교하여 유사한 이미지를 검색하는 내용기반 이미지 검색에서 색상과 모양은 주요 물리적 특징들이다. 지금까지는 색상과 모양을 서로 독립적인 특징으로 분리하여 이용하였지만, 인지적 관점에서 두 특징은 밀접한 관련이 있다. 본 논문에서는 색상과 모양 특징을 동시에 표현하기 위하여 3차원 색상 정보를 2차원 복소수 형식으로 표현하는 복소 색상 모델을 이용하여 색상의 공간적 분포 모양을 기술하는 방법을 제안한다. 복소 이미지를 주파수 변환한 후 저주파 영역의 소수의 계수만으로 복원하는 실험을 통하여 제안된 방법이 색상의 공간적 분포 모양을 효율적으로 표현할 수 있음을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권7호
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• pp.1807-1822
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• 2023

Innovation and rapid increased functionality in user friendly smartphones has encouraged shutterbugs to have picturesque image macros while in work environment or during travel. Formal signboards are placed with marketing objectives and are enriched with text for attracting people. Extracting and recognition of the text from natural images is an emerging research issue and needs consideration. When compared to conventional optical character recognition (OCR), the complex background, implicit noise, lighting, and orientation of these scenic text photos make this problem more difficult. Arabic language text scene extraction and recognition adds a number of complications and difficulties. The method described in this paper uses a two-phase methodology to extract Arabic text and word boundaries awareness from scenic images with varying text orientations. The first stage uses a convolution autoencoder, and the second uses Arabic Character Segmentation (ACS), which is followed by traditional two-layer neural networks for recognition. This study presents the way that how can an Arabic training and synthetic dataset be created for exemplify the superimposed text in different scene images. For this purpose a dataset of size 10K of cropped images has been created in the detection phase wherein Arabic text was found and 127k Arabic character dataset for the recognition phase. The phase-1 labels were generated from an Arabic corpus of quotes and sentences, which consists of 15kquotes and sentences. This study ensures that Arabic Word Awareness Region Detection (AWARD) approach with high flexibility in identifying complex Arabic text scene images, such as texts that are arbitrarily oriented, curved, or deformed, is used to detect these texts. Our research after experimentations shows that the system has a 91.8% word segmentation accuracy and a 94.2% character recognition accuracy. We believe in the future that the researchers will excel in the field of image processing while treating text images to improve or reduce noise by processing scene images in any language by enhancing the functionality of VGG-16 based model using Neural Networks.

• The International Journal of Costume Culture
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• 제5권1호
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• pp.58-66
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• 2002

The objectives of this study are to develope sensibility image scales for Korean traditional motifs by quantitatively measuring their images and preference and to classify them into clusters. Data were collected via a questionnaire from seven hundred twenty five Korean undergraduate students. Re experimental materials were forty eight stimuli of Korean traditional motifs with different categories, interpretation types, composition types, and application objects. The instruments consisted of 7-point polar semantic differential scales of twenty three bipolar adjectives including preference. Data were analyzed by correspondence analysis, cluster analysis, ANOVA and Duncan's multiple range test. Re major results are as follows; image scales for textile patterns and dress designs using Korean traditional motifs were constructed. The axes of sensibility image scales for both textile patterns and dress designs were defined by quality level and degree of simplicity. Second, four clusters on the scale of textile patterns and two clusters on the scale dress designs were identified. Third, in the case of textile Patterns, the preferred cluster had high-quality and classical images, while the cluster that was not preferred had a complex image. In the case of dress designs, the preferred cluster had simple and high-quality images, while the cluster that was not preferred had complex and low-quality images.

• 품질경영학회지
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• 제44권3호
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• pp.527-540
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• 2016

Purpose: The purpose of this study was to propose contrast metric which is based on the human visual perception and thus it can be used to improve the quality of digital images in many applications. Methods: Previous literatures are surveyed, and then the proposed method is modeled based on Human Visual System(HVS) such as multiscale property of the contrast sensitivity function (CSF), contrast constancy property (suprathreshold), color channel property. Furthermore, experiments using digital images are shown to prove the effectiveness of the method. Results: The results of this study are as follows; regarding the proposed contrast measure of complex images, it was found by experiments that HVS follows relatively well compared to the previous contrast measurement. Conclusion: This study shows the effectiveness on how to measure the contrast of complex images which follows human perception better than other methods.