• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.19-26
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• 2009

The microwave exposure device for microwave breast cancer detection consists of RF transceiver and several antennas. The microwave information of object acquired from the microwave exposure device can be calculated permittivity and conductivity by using the inverse scattered analysis. In this paper, we have developed the software for detecting breast cancers based on microwave tomography, by which users not only can check out the existence of breast cancers through the permittivity and conductivity information analysis of the object's internal, but also can analysis easily information for distribution of breast cancers. The developed software provides the function for visualizing the captured permittivity and conductivity information as 2D or 3D color images on which users can easily detect the existence of breast cancers. For more detailed analysis of tomography images, the proposed software also has provided the functions for displaying their cutting profiles as well as position and size information of special area in them.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.459-465
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• 2013

This paper is a study on an object extraction method which using color features of an object and background in the image. A human recognizes an object through the color difference of object and background in the image. So we must to emphasize the color's difference that apply to extraction result in this image. Therefore, we have converted to HSV color images which similar to human visual system from original RGB images, and have created two each other images that applied Median Filter and we merged two Median filtered images. And we have applied the Mean Shift algorithm which a data clustering method for clustering color features. Finally, we have normalized 3 image channels to 1 image channel for binarization process. And we have created object map through the binarization which using average value of whole pixels as a threshold. Then, have extracted major object from original image use that object map.

• Journal of Broadcast Engineering
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• v.22 no.5
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• pp.608-617
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• 2017

Methods of contrast enhancement have problem such as side effect of over-enhancement with non-gaussian histogram distribution, tradeoff enhancement efficiency against brightness preserving. In order to enhance contrast at various histogram distribution, segmentation to region with gaussian distribution and then enhance contrast each region. First, we segment an image into several regions using GMM(Gaussian Mixture Model)fitting by that k-mean clustering and EM(Expectation-Maximization) in $L^*a^*b^*$ color space. As a result region segmentation, we get the region map and probability map. Then we apply local contrast enhancement algorithm that mean shift to minimum overlapping of each region and preserve brightness histogram equalization. Experiment result show that proposed region based contrast enhancement method compare to the conventional method as AMBE(AbsoluteMean Brightness Error) and AE(Average Entropy), brightness is maintained and represented detail information.

• The Journal of the Korea Contents Association
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• v.7 no.1
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• pp.40-47
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• 2007

In the protein macro array image, it is important to find out the feature of the each protein chip. A decision error by the personal sense of sight occurred from long time observation while making an experiment in many protein chip image. So the feature extraction is needed by a simulator. In the case of feature analysis for macro array scan image the efficiency is maximized. In the fluorescence scan image, the response for each cell have been depend on R, G, B distribution of color image. But it is difficult to be classified as one color feature in the case of mixed color image. In this paper, the response color of a protein chip is classified according to the fuzzy integral value with respect to fuzzy measure as the user desired color. The result of the experiment for the macro array fluorescence image with the Scan Array 5000 shows that the proposed method using the fuzzy integral is important fact to be make decision for the ambiguous color.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.12-20
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• 2011

In this paper, we propose an efficient object detection and classification algorithm for video surveillance applications. Previous researches mainly concentrated either on object detection or classification using particular type of feature e.g., Scale Invariant Feature Transform (SIFT) or Speeded Up Robust Feature (SURF) etc. In this paper we propose an algorithm that mutually performs object detection and classification. We combinedly use heterogeneous types of features such as texture and color distribution from local patches to increase object detection and classification rates. We perform object detection using spatial clustering on interest points, and use Bag of Words model and Naive Bayes classifier respectively for image representation and classification. Experimental results show that our combined feature is better than the individual local descriptor in object classification rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.1C
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• pp.64-71
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• 2003

In this paper, we proposed an algorithm that shorten coding time maintaining image quality in JPEG2000, which is the standard, of still image compression. This method encodes only the bit plane selected as appropriate truncation point for output bitstream, obtained from estimation of frequency distribution for whole image. Wavelet characterized by multi-resolution has vertical, horizontal, and diagonal frequency components for each resolution. The frequency interrelation addressed above is maintained thorough whole level of resolution and represents the unique frequency characteristics for input image. Thus, using the frequency relation at highest level, we can pick the truncation point for the compression time decrease by estimating code bits at encoding each code block. Also, we reduced the encoding time using simply down sampling instead of low-pass filtering at low-levels which are not encoded in color component of lower energy than luminance component. From the proposed algorithm, we can reduce about 15~36% of encoding time maintaining PSNR 30$\pm$0.5㏈.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.1-8
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• 2003

Various methods have been studying to maintain and apply the multimedia inform abruptly increasing over all social fields, in recent years. For retrieval of still images, we is implemented content-based image retrieval system in this paper that make possible to retrieve similar objects from image database after segmenting query object from background if user request query. Query image is processed median filtering to remove noise first and then object edge is detected it by canny edge detection. And query object is segmented from background by using convex hull. Similarity value can be obtained by means of histogram intersection with database image after securing color histogram from segmented image. Also segmented image is processed gray convert and wavelet transform to extract spacial gray distribution and texture feature. After that, Similarity value can be obtained by means of banded autocorrelogram and energy. Final similar image can be retrieved by adding upper similarity values that it make possible to not only robust in background but also better correct object retrieval by using object segmentation method.

• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.492-502
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• 2011

20 fossil sites of numerous fossil sites in Korea have been designated as Natural Monument for protection and conservation. Many of the sites which is located at the coastal area have been gradually disfigured by natural weathering, erosion and human activity. Thus the conservation of the original form and the documentation for the original figure are necessary. In this study, we applied 3D digital documentation to Natural Monument No. 394, Haenam Uhangri dinosaur, pterosaur, and bird footprint fossil site, for maintaining the original form of the dinosaur footprints. We were able to obtain the 3D digital data on two dinosaur footprint sites, a high resolution distributional map, and more accurate digital data of the dinosaur footprints applied the rendering method by ambient occlusion. 3D digital data on the dinosaur footprints is worth for the conservation and research data, moreover content for applying to the various fields such as to make 3D brochure, interactive contents, and so on.

• Korean Journal of Optics and Photonics
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• v.28 no.1
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• pp.1-8
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• 2017

A method for inspecting defects in display substrates utilizing Fourier optics is proposed in this paper. A cost-effective inspection system can be realized with the proposed method, because it does not require a high-magnification microscope. Also, the proposed method can avoid tight tolerance for variations in displacement between substrate and camera, which is stems from shallow depth of field of the high-magnification microscope. In addition, possible damage caused by collisions between substrate and the inspection equipment can be avoided. The decision algorithm can be simpler than for a conventional inspection system, because spatial shift of periodic substrate patterns does not affect the intensity distribution of the diffracted light, by the Fourier transform property. The proposed method is explained with numerical studies, and experiments are carried out to check its feasibility for color-filter substrates of a liquid-crystal display.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.179-187
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• 2008

In this paper, we apply a set of algorithms to classily normal and cancer nucleus from uterine cervical pap-smear images. First, we use lightening compensation algorithm to restore color images that have defamation through the process of obtaining $1{\times}400$ microscope magnification. Then, we remove the background from images with the histogram distributions of RGB regions. We extract nucleus areas from candidates by applying histogram brightness, Kapur method, and our own 8-direction contour tracing algorithm. Various binarization, cumulative entropy, masking algorithms are used in that process. Then, we are able to recognize normal and cancer nucleus from those areas by using three morphological features - directional information, the size of nucleus, and area ratio - with fuzzy membership functions and deciding rules we devised. The experimental result shows our method has low false recognition rate.