• Title/Summary/Keyword: 질감의 차이

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Texture Descriptor for Texture-Based Image Retrieval and Its Application in Computer-Aided Diagnosis System (질감 기반 이미지 검색을 위한 질감 서술자 및 컴퓨터 조력 진단 시스템의 적용)

  • Saipullah, Khairul Muzzammil;Peng, Shao-Hu;Kim, Deok-Hwan
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.4
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    • pp.34-43
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    • 2010
  • Texture information plays an important role in object recognition and classification. To perform an accurate classification, the texture feature used in the classification must be highly discriminative. This paper presents a novel texture descriptor for texture-based image retrieval and its application in Computer-Aided Diagnosis (CAD) system for Emphysema classification. The texture descriptor is based on the combination of local surrounding neighborhood difference and centralized neighborhood difference and is named as Combined Neighborhood Difference (CND). The local differences of surrounding neighborhood difference and centralized neighborhood difference between pixels are compared and converted into binary codewords. Then binomial factor is assigned to the codewords in order to convert them into high discriminative unique values. The distribution of these unique values is computed and used as the texture feature vectors. The texture classification accuracies using Outex and Brodatz dataset show that CND achieves an average of 92.5%, whereas LBP, LND and Gabor filter achieve 89.3%, 90.7% and 83.6%, respectively. The implementations of CND in the computer-aided diagnosis of Emphysema is also presented in this paper.

Rotation Transformation Invariant Texture Classification for Object Recognition of Surveillance Camera Image (감시 카메라 영상의 객체 인식을 위한 회전 변화에 강인한 질감 분류)

  • Kim, Won-Hee;Park, Seong-Mo;Kim, Jong-Nam
    • Proceedings of the Korea Information Processing Society Conference
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    • 2009.04a
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    • pp.171-172
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    • 2009
  • 질감 분류 기술은 패턴인식과 컴퓨터 비전 분야에서 널리 사용되는 기술로서, 최근 들어서는 감시 카메라 시스템에서의 정확한 객체 인식을 위한 회전 변화에 강인한 질감 분류 연구가 진행되고 있다. 본 논문에서는 순환 가보 웨이블렛 필터를 이용한 회전 변환에 강인한 질감 분류 방법을 제안한다. 제안하는 방법은 순환 가보 웨이블렛 필터링된 영상에서 전역 및 지역 특징 벡터를 계산하고 특징 벡터의 차이를 이용한 유사도 측정 판별식으로 질감 분류를 수행한다. Brodatz 질감 앨범을 이용한 실험에서 기존의 방법들보다 2~6% 향상된 질감 분류 비율을 확인할 수 있었다. 제안하는 방법은 질감 기반 객체 인식에 관련된 응용 분야에서 유용하게 사용될 수 있다.

Structural and Textural Characteristics of Egg Custard with Soused Shrimp Juice (새우젓국물 첨가에 따른 알찜의 구조 및 질감에 관한 연구)

  • 배영희
    • Korean journal of food and cookery science
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    • v.9 no.4
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    • pp.303-307
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    • 1993
  • Structural and textural characteristics of egg custard with 1.5ft sodium chloride as salt or soused shrimp juice were investigated by SEM, texturometer and sensory evaluation.: 1. Egg custard without sodium chloride showed flat, crosslinkaged structure and no pores. : but the addition of salt or soused shrimp juice developed much of round pores and smooth walls. 2. There were significant difference in hardness between without sodium chloride group and boiled soused shrimp juice group. 3. there were significant difference in appearance, taste and texture, but flavor and total acceptability did not showed significant difference in preference test. In discriminating test, swellness, softness, flavor, color, holes and hardness were important factors affecting the preference to determine the characteristics of egg custard.

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Image Retrieval Using Combination of Color and Multiresolution Texture Features (칼라 및 다해상도 질감 특징 결합에 의한 영상검색)

  • Chun Young-deok;Sung Joong-ki;Kim Nam-chul
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.9C
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    • pp.930-938
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    • 2005
  • We propose a content-based image retrieval(CBIR) method based on an efncient combination of a color feature and multiresolution texture features. As a color feature, a HSV autocorrelograrn is chosen which is blown to measure spatial correlation of colors well. As texture features, BDIP and BVLC moments are chosen which is hewn to measure local intensity variations well and measure local texture smoothness well, respectively. The texture features are obtained in a wavelet pyramid of the luminance component of a color image. The extracted features are combined for efficient similarity computation by the normalization depending on their dimensions and standard deviation vectors. Experimental results show that the proposed method yielded average $8\%\;and\;11\%$ better performance in precision vs. recall than the method using BDIPBVLC moments and the method using color autocorrelograrn, respectively and yielded at least $10\%$ better performance than the methods using wavelet moments, CSD, color histogram. Specially, the proposed method shows an excellent performance over the other methods in image DBs contained images of various resolutions.

Rotation-Invariant Texture Classification Using Gabor Wavelet (Gabor 웨이블릿을 이용한 회전 변화에 무관한 질감 분류 기법)

  • Kim, Won-Hee;Yin, Qingbo;Moon, Kwang-Seok;Kim, Jong-Nam
    • Journal of Korea Multimedia Society
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    • v.10 no.9
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    • pp.1125-1134
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    • 2007
  • In this paper, we propose a new approach for rotation invariant texture classification based on Gabor wavelet. Conventional methods have the low correct classification rate in large texture database. In our proposed method, we define two feature groups which are the global feature vector and the local feature matrix. The feature groups are output of Gabor wavelet filtering. By using the feature groups, we defined an improved discriminant and obtained high classification rates of large texture database in the experiments. From spectrum symmetry of texture images, the number of test times were reduced nearly 50%. Consequently, the correct classification rate is improved with $2.3%{\sim}15.6%$ values in 112 Brodatz texture class, which may vary according to comparison methods.

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Study on evaluating the significance of 3D nuclear texture features for diagnosis of cervical cancer (자궁경부암 진단을 위한 3차원 세포핵 질감 특성값 유의성 평가에 관한 연구)

  • Choi, Hyun-Ju;Kim, Tae-Yun;Malm, Patrik;Bengtsson, Ewert;Choi, Heung-Kook
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.10
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    • pp.83-92
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    • 2011
  • The aim of this study is to evaluate whether 3D nuclear chromatin texture features are significant in recognizing the progression of cervical cancer. In particular, we assessed that our method could detect subtle differences in the chromatin pattern of seemingly normal cells on specimens with malignancy. We extracted nuclear texture features based on 3D GLCM(Gray Level Co occurrence Matrix) and 3D Wavelet transform from 100 cell volume data for each group (Normal, LSIL and HSIL). To evaluate the feasibility of 3D chromatin texture analysis, we compared the correct classification rate for each of the classifiers using them. In addition to this, we compared the correct classification rates for the classifiers using the proposed 3D nuclear texture features and the 2D nuclear texture features which were extracted in the same way. The results showed that the classifier using the 3D nuclear texture features provided better results. This means our method could improve the accuracy and reproducibility of quantification of cervical cell.

Texture Analysis of Carcinoma Cell Tissue Image based on Wavelet Transform (Wavelet 변환에 기반한 암세포 조직 영상의 질감 분석)

  • 최현주;이병일;이연숙;최홍국
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2000.08a
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    • pp.305-308
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    • 2000
  • 암의 진행 정도를 판단하기 위한 암세포 조직영상의 분석은 그 대상이 되는 영상의 다양성과 잡음으로 인해 정확한 분석이 어렵다. 특히, 암의 진행 정도를 판단하는데 있어서 중요한 요인인 세포핵의 variation에 따른 order/disorder 정도를 객관적 수치로 정량화하기 위해서는, 각 기(stage)에 따른 암의 진행정도를 가장 잘 나타낼 수 있는 특징값 추출이 필수적이다. 본 논문에서는 가장 유효한 특징값을 추출하기 위하여, 공간 영역과 주파수 영역에서 그 지역적 특징을 잘 나타내는 wavelet 변환을 적용한 후, 분할 된 서브 밴드 중 고대역 서브 밴드에서 질감 특징을 추출하고, 추출 된 질감 특징값들이 암의 진행 정도에 따른 각 집단간에 유의한 차이를 나타내는지에 대한 유의성을 검증하기 위하여, 다변량 통계학적 분석 방법을 사용하여 비교분석 하였다.

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A Texture Classification Based on LBP by Using Intensity Differences between Pixels (화소간의 명암차를 이용한 LBP 기반 질감분류)

  • Cho, Yong-Hyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.5
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    • pp.483-488
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    • 2015
  • This paper presents a local binary pattern(LBP) for effectively classifying textures, which is based on the multidimensional intensity difference between the adjacent pixels in the block image. The intensity difference by considering the a extent of 4 directional changes(verticality, horizontality, diagonality, inverse diagonality) in brightness between the adjacent pixels is applied to reduce the computation load as a results of decreasing the levels of histogram for classifying textures of image. And the binary patterns that is represented by the relevant intensities within a block image, is also used to effectively classify the textures by accurately reflecting the local attributes. The proposed method has been applied to classify 24 block images from USC Texture Mosaic #2 of 128*128 pixels gray image. The block images are different in size and texture. The experimental results show that the proposed method has a speedy classification and makes a free size block images classify possible. In particular, the proposed method gives better results than the conventional LBP by increasing the range of histogram level reduction as the block size becomes larger.

Effect of raw soy flour addtion to Jeung-Pyun pizza on fermentation time and viscosity of batters and texture and general desirability of Jeung-Pyun pizza (날콩가루를 첨가한 증편 피자판 개발에 관한 연구)

  • Yoon, Sun;Lee, Chun-Ja; Park, Hye-Won;Myoung, Chun-Ok;Choi, Eun-Jung;Lee Ji-Jung
    • Korean journal of food and cookery science
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    • v.16 no.3
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    • pp.267-271
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    • 2000
  • The present study was designed to develop the standardized formula for the preparation Jeung-Pyun with added raw soy flour and to investigate the applicability of Jeung-Pyun as the substitute of regular pizza crust made with wheat flour. The effect of adding raw soy flour at 3%, 5% level on fermentation time and viscosity of batters and texture and general desirability of Jeung-Pyun pizza were also studied. As the level of raw soy flour was increased the time required for 1 st and 2nd fermentation decreased and viscosity of batters increased significantly. Jeung-Pyun crust after steaming found to have appropriate texture and form for a substitute of wheat flour pizza crust. Texture parameters determined by QST showed that Jeung-Pyun crust with added raw soy flour had lower values in hardness, cohesiveness and gumminess without any significant difference. However, chewiness of 5% raw soy flour group was significantly lower than control group. Texture of Jeung-Pyun crust and general desirability of Jeung-Pyun pizza were determined by sensory evaluation. Textural parameters of Jeung-Pyun crust were evaluated on the basis of hardness, cohesiveness, adhesiveness, tenderness and wetness. As a result of sensory evaluation Jeung-Pyun crust made with 5% raw soy flour had significant lower values in hardness, cohesiveness, tenderness and wetness than the control. However, the textural parameters between control and 3 % raw soy flour group were not significantly different. Jeung-Pyun pizza with topping were evaluated by sensory panel. Jeung-Pyun pizza made with 3% raw soy flour received the highest score in apperance and general desirability without any significant difference. 5% raw soy flour group had significantly lower score in general desirability among 3 treatment groups. In conclusion, Jeung-Pyun crust made by traditional Jeung-Pyun preparation method will be a good alternative to replace wheat flour pizza crust. Adding raw soy flour at 3% level did not affect the quality of Jeung-Pyun crust and had an effect of promoting fermentation. Jeung-Pyun Pizza crust was expected to have tender texture and slower retrogradation rate than regular pizza crust with wheat flour.

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