• Title/Summary/Keyword: Color Similarity

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An Effective Relevance Feedbackbased Image Retrieval using Color and Texture

  • Jung, Sung-Hwan
    • Journal of Korea Multimedia Society
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    • v.6 no.4
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    • pp.746-752
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    • 2003
  • In this paper, we proposed an image retrieval system with a simple and effective relevance feedback, called RAP(Reward and Punishment) algorithm. First, color and texture features were extracted from the images. Next, the extracted feature values were used for image retrieval in various forms. We applied the relevance feedback to the initial retrieved images from the image retrieval system, and compared its result with that of the conventional system. In the experiment using the test image database of 16 class 512 images, the proposed system showed the better retrieval performance of about 10∼l7 % than that of the conventional INRIA system in each relevance feedback step.

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A new demosaicing method based on trilateral filter approach (세방향 필터 접근법에 기반한 새로운 디모자익싱 기법)

  • Kim, Taekwon;Kim, Kiyun
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.11 no.4
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    • pp.155-164
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    • 2015
  • In this paper, we propose a new color interpolation method based on trilateral filter approach, which not only preserve the high-frequency components(image edge) while interpolating the missing raw data of color image(bayer data pattern), but also immune to the image noise components and better preserve the detail of the low-frequency components. The method is the trilateral filter approach applying a gradient to the low frequency components of the image signal in order to preserve the high-frequency components and the detail of the low-frequency components through the measure of the freedom of similarity among adjacent pixels. And also we perform Gaussian smoothing to the interpolated image data in order to robust to the noise. In this paper, we compare the conventional demosaicing algorithm and the proposed algorithm using 10 test images in terms of hue MAD, saturation MAD and CPSNR for the objective evaluation, and verify the performance of the proposed algorithm.

Shape region segmentation method using color and edge characteristics of moving images (동영상의 컬러 및 에지 정보에 기초한 Shape영역 segmentation 기법)

  • Park, Jin-Nam;Lee, Jae-Duck;Yoon, Sung-Soo;Huh, Young
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.145-148
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    • 2002
  • A study on image searching and management techniques is actively developed by user requirements for multimedia information that are existing as images, audios, texts data from various information processing devices. We had been studied an automatical shape region segmentation method using color. distribution and edge characteristics of moving images for. contents-base description. The Proposed method uses a color information quantized on human visual system and extracts overlapped regions to be matched by using edge characteristics of the image frame. The performance of the proposed method is represented by similarity for comparison to a segmented image and original image.

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Trademark Image Retrieval System (상표 영상 검색 시스템)

  • Shin, Seong-Yoon;Baik, Seong-Eun;Pyo, Seong-Bae;Rhee, Yang-Won
    • KSCI Review
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    • v.15 no.1
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    • pp.185-190
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    • 2007
  • An image retrieval system is a piece of software that searches identical or similar images based on various image-specific features. This paper proposes a trademark image retrieval system that uses image colors and forms. In the proposed system, input images are segmented into several other regions, and color distribution histograms for different regions are extracted for use as color information. The proposed system uses form information through the preprocessing process such as boundary surface extraction, centroid extraction, angular sampling and, and through calculating the sums of the distances between the centroid and the boundary surfaces, standard deviations, and the ratios between long and short axes. Like this, the color and form information extracted is used to perform retrieval through measuring similarity.

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Face Region Detection Algorithm using Fuzzy Inference (퍼지추론을 이용한 얼굴영역 검출 알고리즘)

  • Jung, Haing-Sup;Lee, Joo-Shin
    • Journal of Advanced Navigation Technology
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    • v.13 no.5
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    • pp.773-780
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    • 2009
  • This study proposed a face region detection algorithm using fuzzy inference of pixel hue and intensity. The proposed algorithm is composed of light compensate and face detection. The light compensation process performs calibration for the change of light. The face detection process evaluates similarity by generating membership functions using as feature parameters hue and intensity calculated from 20 skin color models. From the extracted face region candidate, the eyes were detected with element C of color model CMY, and the mouth was detected with element Q of color model YIQ, the face region was detected based on the knowledge of an ordinary face. The result of experiment are conducted with frontal face color images of face as input images, the method detected the face region regardless of the position and size of face images.

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Object-Based Image Retrieval Using Color Adjacency and Clustering Method (컬러 인접성과 클러스터링 기법을 이용한 객체 기반 영상 검색)

  • Lee Hyung-Jin;Park Ki-Tae;Moon Young-Shik
    • The KIPS Transactions:PartB
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    • v.12B no.1 s.97
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    • pp.31-38
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    • 2005
  • This paper proposes an object-based image retrieval scheme using color adjacency and clustering method. Color adjacency features in boundary regions are utilized to extract candidate blocks of interest from image database and a clustering method is used to extract the regions of interest(ROI) from candidate blocks of interest. To measure the similarity between the query and database images, the histogram intersection technique is used. The color pair information used in the proposed method is robust against translation, rotation, and scaling. Consequently, experimental results have shown that the proposed scheme is superior to existing methods in terms of ANMRR.

An Analysis on the Street Fashion Trend of the Adolescent in Pusan (부산지역 청소년의 스트리트 패션 경향 분석)

  • Noh, Kyung-Hye;Lee, Kyoung-Hee
    • Fashion & Textile Research Journal
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    • v.4 no.2
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    • pp.176-187
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    • 2002
  • The aim of this research is to establish basic materials for fashion merchandising by observing the street fashion of the juveniles and by analyzing their wearing, coordination and fashion trend. We have taken the photograph of the street fashion of 202 male teenagers and 265 female teenagers in Busan, and analyzed in the category of style, item, color, pattern, materials, hair style, shoes and accessories. We have concluded that the most frequent items were shirts (male), turtle neck (female) and jeans. The main style was casual just as jumper-look, sweater-look, gardigan-look. The typical female fashions that were hip-hop-look, twin neat-look, trench coat-look, were more various than male. For the color coordination, contrast color coordination was more dominant than similarity color coordination. Dominant patterns were solid, and also check and stripe patterns were frequently found in upper garment. The representative materials were soft for upper garment, and hard for trousers. Male teenagers prefer middle-length hair style and female teenagers prefer long hair style. The juveniles in Busan are wearing sports shoes and leather shoes in similar frequency. Their favorite accessories are bag, muffler and hat.

Variation of Shell Color in Three Geographic White Clam ($Meretrix$ $lusoria$) Populations of the Yellow Sea

  • Yoon, Jong-Man;Park, Kyung-Il;Choi, Sang-Hoon
    • Development and Reproduction
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    • v.16 no.1
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    • pp.47-51
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    • 2012
  • Genomic DNAs (gDNAs) were isolated from the hard clam ($Meretrix$ $lusoria$, Roding, 1798) populations of Gunsan located in the Yellow Sea of the Korean peninsula. Genetic distances among different individuals of the LSCP (light shell color population) population of the hard clam (lane 1-11), GSCP (grey shell color population) population of the hard clam (lane 12-22) and DSCP (dark shell color population) population of the hard clam (lane 23-33), respectively, were generated using Systat version 10 according to the bandsharing values and similarity matrix. The dendrogram, generated by seven reliable oligonucleotides primers, indicates 3 genetic clusters. LSCP population could be evidently discriminated with the other two populations among three populations. The longest genetic distance (0.801) was found to exist between individuals in the two populations, between individuals' no. 33 of the DSCP population and no. 06 of the LSCP population. The higher fragment sizes (>2,000 bp) are much more observed in the GSCP population. Three hard clam populations can be clearly distinguished, especially, by their morphological characters and PCR-based approach.

A Study of an Image Retrieval Method using Binary Subimage (이진 부분영상을 이용한 영상 검색 기법에 관한 연구)

  • 정순영;최민규;남재열
    • Journal of the Institute of Convergence Signal Processing
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    • v.2 no.1
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    • pp.28-37
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    • 2001
  • An image retrieval method combining shape information of 2-dimension color histograms with color information of HSI color histograms is proposed in this paper. In addition, the proposed method can find location information of image through the comparison of similarity among subimages. The suggested retrieval method applies the location information to shape and color information and can retrieve region information which is hard to distinguish in the binary image. Some simulation results show that it works very well in the behalf of precision/recall graph compare with conventional method which uses color histogram. Especially, the proposed method brought well effects such as rotations and transitions of the objects in an image was found.

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Development of Deep Recognition of Similarity in Show Garden Design Based on Deep Learning (딥러닝을 활용한 전시 정원 디자인 유사성 인지 모형 연구)

  • Cho, Woo-Yun;Kwon, Jin-Wook
    • Journal of the Korean Institute of Landscape Architecture
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    • v.52 no.2
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    • pp.96-109
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    • 2024
  • The purpose of this study is to propose a method for evaluating the similarity of Show gardens using Deep Learning models, specifically VGG-16 and ResNet50. A model for judging the similarity of show gardens based on VGG-16 and ResNet50 models was developed, and was referred to as DRG (Deep Recognition of similarity in show Garden design). An algorithm utilizing GAP and Pearson correlation coefficient was employed to construct the model, and the accuracy of similarity was analyzed by comparing the total number of similar images derived at 1st (Top1), 3rd (Top3), and 5th (Top5) ranks with the original images. The image data used for the DRG model consisted of a total of 278 works from the Le Festival International des Jardins de Chaumont-sur-Loire, 27 works from the Seoul International Garden Show, and 17 works from the Korea Garden Show. Image analysis was conducted using the DRG model for both the same group and different groups, resulting in the establishment of guidelines for assessing show garden similarity. First, overall image similarity analysis was best suited for applying data augmentation techniques based on the ResNet50 model. Second, for image analysis focusing on internal structure and outer form, it was effective to apply a certain size filter (16cm × 16cm) to generate images emphasizing form and then compare similarity using the VGG-16 model. It was suggested that an image size of 448 × 448 pixels and the original image in full color are the optimal settings. Based on these research findings, a quantitative method for assessing show gardens is proposed and it is expected to contribute to the continuous development of garden culture through interdisciplinary research moving forward.