• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.1
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• pp.104-115
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• 2001

A new content-based color image retrieval method integrating the features of the color adjacency and the gradient is proposed in this paper. As the most used feature of color image, color histogram has its own advantages that it is invariant to the changes in viewpoint and the rotation of the image etc., and the computation of the feature is simple and fast. However, it is difficult to distinguish those different images having similar color distributions using histogram-based image retrieval, because the color histogram is generated on uniformly quantized colors and the histogram itself contains no spatial information. And another shortcoming of the histogram-based image retrieval is the storage of the features is usually very large. In order to prevent the above drawbacks, the gradient that is the largest color difference of neighboring pixels is calculated in the proposed method instead of the uniform quantization which is commonly used at most histogram-based methods. And the color adjacency information which indicates major color composition feature of an image is extracted and represented as a binary form to reduce the amount of feature storage. The two features are integrated to allow the retrieval more robust to the changes of various external conditions.

• Journal of Korean Society of Forest Science
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• v.76 no.1
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• pp.41-50
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• 1987

The various conditions of photographs, especially kinds of films, combinated filters and seasons are important factors for forestry purpose aerial photography. In this paper the variations of tones were compared between color and color infrared, panchromatic black and white and infrared black and white, and among false color photographic images created by using 3 kinds of filters when prints are made. Color infrared film was good for identifying tree species, for its spectral signatures had a greater range of tones and hues than color signatures. In that case taken in May were more effective than taken April. False color photographs were not so good as color photographs because they were mostly dark and indistinct. Infrared black and white film with medium red filter showed potential for separating broad-leaved forests from conifers. MSS composed photographs, when composed with proper bands and densities, were proved useful for distinguishing land use types but not applicable to more detailed practices such as forest type separation and tree species identification.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.1-10
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• 2005

Content-based image retrieval systems are being actively investigated owing to their ability to retrieve images based on the actual visual content rather than by manually associated textual descriptions. In this paper, we propose a novel approach for image retrieval based on edge structural features using edge correlogram and color coherence vector. After color vector angle is applied in the pre-processing stage, an image is divided into two image parts (high frequency image and low frequency image). In low frequency image, the global color distribution of smooth pixels is extracted by color coherence vector, thereby incorporating spatial information into the proposed color descriptor. Meanwhile, in high frequency image, the distribution of the gray pairs at an edge is extracted by edge correlogram. Since the proposed algorithm includes the spatial and edge information between colors, it can robustly reduce the effect of the significant change in appearance and shape in image analysis. The proposed method provides a simple and flexible description for the image with complex scene in terms of structural features of the image contents. Experimental evidence suggests that our algorithm outperforms the recently histogram refinement methods for image indexing and retrieval. To index the multidimensional feature vectors, we use R*-tree structure.

• Proceedings of the KSMRM Conference
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• 2002.11a
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• pp.133-133
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• 2002

Purpose： The purpose of paper is to implement software to visualize brain fiber tract using a 24-bit color coding scheme and to test its feasibility. Materials and Methods： MR imaging was performed on GE 1.5 T Signa scanner. For diffusion tensor image, we used a single shot spin-echo EPI sequence with 7 non-colinear pulsed-field gradient directions： (x, y, z)：(1,1,0),(-1,1,0),(1,0,1),(-1,0,1),(0,1,1),(0,1,-1) and without diffusion gradient. B-factor was 500 sec/$\textrm{mm}^2$. Acquisition parameters are as follows： TUTE=10000ms/99ms, FOV=240mm, matrix=128${\times}$128, slice thickness/gap=6mm/0mm, total slice number=30. Subjects consisted of 10 normal young volunteers (age：21∼26 yrs, 5 men, 5 women). All DTI images were smoothed with Gaussian kernel with the FWHM of 2 pixels. Color coding schemes for visualization of directional information was as follows. HSV(Hue, Saturation, Value) color system is appropriate for assigning RGB(Red, Green, and Blue) value for every different directions because of its volumetric directional expression. Each of HSV are assigned due to (r,$\theta$,${\Phi}$) in spherical coordinate. HSV calculated by this way can be transformed into RGB color system by general HSV to RGB conversion formula. Symmetry schemes： It is natural to code the antipodal direction to be same color(antipodal symmetry). So even with no symmetry scheme, the antipodal symmetry must be included. With no symmetry scheme, we can assign every different colors for every different orientation.(H =${\Phi}$, S=2$\theta$/$\pi$, V=λw, where λw is anisotropy). But that may assign very discontinuous color even between adjacent yokels. On the other hand, Full symmetry or absolute value scheme includes symmetry for 180$^{\circ}$ rotation about xy-plane of color coordinate (rotational symmetry) and for both hemisphere (mirror symmetry). In absolute value scheme, each of RGB value can be expressed as follows. R=λw｜Vx｜, G=λw｜Vy｜, B=λw｜Vz｜, where (Vx, Vy, Vz) is eigenvector corresponding to the largest eigenvalue of diffusion tensor. With applying full symmetry or absolute value scheme, we can get more continuous color coding at the expense of coding same color for symmetric direction. For better visualization of fiber tract directions, Gamma and brightness correction had done. All of these implementations were done on the IDL 5.4 platform.

• Journal of Korea Multimedia Society
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• v.23 no.7
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• pp.812-818
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• 2020

Cervical cancer is the second most common female cancer in the world. In Korea, cervical cancer accounts for 13 percent of female cancers and 4,200 cases occur annually[1]. The purpose of this study is to use a deep learning model to identify the possibility of lesions in the cervix and to evaluate the efficient image preprocessing in order to diagnose diverse types of cervix in form. The study used 4,107 normal photographs of uterine cervix and 6,285 abnormal photographs of uterine cervix. Two types of image preprocessing were resized to square. The methods are cropping based on height and filling the space up and down with black images. In addition, all images were resampled to 256×256. The average accuracy of cropped cases is 94.15%. The average accuracy of the filled cases is 93.41%. According to the study, the model performance of cropped data was slightly better. But there were several images that were not accurately classified. Therefore, the additional experiment with pre-treatment process based on cropping is needed to cover images of the cervix in more detail.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.281-288
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• 2009

This paper proposes a novel algorithm for the efficient classification and annotation of medical images, especially X-ray images. Since X-ray images have a bright foreground against a dark background, we need to extract the different visual descriptors compare with general nature images. In this paper, a Color Structure Descriptor (CSD) based on Harris Corner Detector is only extracted from salient points, and an Edge Histogram Descriptor (EHD) used for a textual feature of image. These two feature vectors are then applied to a multi-class Support Vector Machine (SVM), respectively, to classify images into one of 20 categories. Finally, an image has the Annotation Code Array based on the pre-defined hierarchical relations of categories and priority code order, which is given the several optimal keywords by the Annotation Code Array. Our experiments show that our annotation results have better annotation performance when compared to other method.

• Journal of the Korean Society of Costume
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• v.61 no.1
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• pp.20-33
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• 2011

This study aims to analyze the expressive aspect of men's shirts through examining the characteristics of men's shirts with the trend of men's clothing well represented and considering the image based on high fashion. As a method of study, I have conducted the theoretical study through the literature data, and the content analysis through photographs from S/S collection in 2005 to F/W collection in 2010. Especially, in the recent men's shirts, the materials of glossy silk, wavering chiffon and jersey tend to appear and various images are represented with the tasteful decoration such as ruffle, pin tuck and embroidery together with pastel color. Thus, the result of this study is as follows: Firstly, the masculine and romantic images are researched as the image emphasizing the beautiful and soft masculine beauty which doesn't lose the masculinity even though they are seasonedwith the feminine elements. Soft masculine beauty is emphasized by using romantic image decoration of frills, beads and pin tuck or silk, jersey and openwork materials etc. Secondly, practical fusion images have been studied as the images emphasizing the freshness with practicality through grafting more than two items onto one shirt. Many designs have appeared representing new shapes by grafting more than two items onto one shirt or obscuring the border line between the items. Thirdly, the avant-garde chic images have been researched as the image emphasizing the chick image through representing unique and odd designs by excessively expressing the silhouette in general shapes of shirts. I come. to find that the mainly the designs, emphasizing the uniqueness and the distinction with transformed shapes of sleeves, cuffs and the length of shirts in exaggerated manners, are appearing. Thus, I intend to provide a reference material which will be useful for the newly created design and researches of figurative characteristics in the future fashion.

• Journal of Broadcast Engineering
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• v.16 no.4
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• pp.602-613
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• 2011

In this paper, we propose a hybrid stereoscopic camera system which acquires and utilizes stereoscopic images from two different camera modules, the main-camera module and the sub-camera module. Hybrid stereoscopic camera can effectively reduce the price and the size of a stereoscopic camera by using a relatively small and cheap sub-camera module such as a mobile phone camera. Images from the two different camera modules are very different from each other in aspects of color, angle of view, scale, resolution and so on. The proposed system performs an efficient hybrid stereoscopic image registration algorithm that transforms hybrid stereoscopic images into normal stereoscopic images based-on camera geometry. As experimental results, the registered stereoscopic images and applications of the proposed system are shown to demonstrate the performance and the functionality of the proposed camera system.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.1 s.13
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• pp.87-95
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• 1999

The min object of this study was to prove the effectiveness of PCA(principal component analysis) merged images produced by PCA method using high resolution IRS-1C PAN data and multispectral Landsat TM data A sample data which has ten classes was generated for evaluation of the overall classification accuracy. In result, merged sample image which TM13457 bands with IRS-1C PAN data by PCA method showed best result (95.1%). Especially, the largest improve (6.2%) in classification accuracy was resulted when IRS-1C PAN data was merged with TM123457 or TM13457 images. In addition, landuse classification accuracy of the PCA merged images was improved (5.16%) than original color composite images of Landsat TM data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.816-822
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• 2016

Content-Based image retrieval is a method to search by image features such as local color, texture, and other image content information, which is different from conventional tag or labeled text-based searching. In real life data, the number of images having tags or labels is relatively small, so it is hard to search the relevant images with text-based approach. Existing image search method only based on image feature similarity has limited performance and does not ensure that the results are what the user expected. In this study, we propose and validate a machine learning based approach to improve the performance of the image search engine. We note that when users search relevant images with a query image, they would expect the retrieved images belong to the same category as that of the query. Image classification method is combined with the traditional image feature similarity method. The proposed method is extensively validated on a public PASCAL VOC dataset consisting of 11,530 images from 20 categories.