• Journal of Biomedical Engineering Research
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• v.27 no.3
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• pp.125-130
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• 2006

The number of the living endothelial cells and the shape of those are very import clinical parameters for the evaluation of the quality of cornea. In this paper, we developed the automated endothelial cell counting and shape analysis algorithm for a confocal microscope. Since, the endothelial images from the confocal microscope has a non-uniform illumination and low contrast between cell boundaries and cell bodies, it is very difficult to segment the cells from the endothelial images. To cope with these difficulties, we proposed the new two stage image processing algorithm. At first stage algorithm, we used a high-pass filter and histogram equalization to compensate the non-uniform brightness pattern and a morphological filter and a watershed method are applied to detect the boundary of cells. From this stage, we could count the number of cells in an endothelial image. At second stage algorithm, we used a Voronoi diagram method to classify the shape of cells. This cell shape analysis and the percent of hexagonal cells are very sensitive in detecting the early endothelium damage. To evaluate the performance of the proposed system, we p개cessed seven endothelial images obtained using a confocal microscope. The proposed system correctly counted 95.5% cells and classified 92.0% of hexagonal cell shapes. This result is better than any others in this research area.

• Korean Institute of Interior Design Journal
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• v.23 no.1
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• pp.143-151
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• 2014

Nowadays, space branding becomes more important since it reflects and synthesizes the diverse experiences of the consumer. The objective of the research is to present the new possibilities that space branding offers by analyzing the brand strategy and the design characteristics of branded hotels, which are being projected as constructed branded environments. By integrating the brand with visible or invisible elements of the hotel, such as unique space planning, service, and consumer experience, a branded hotel can be a good vehicle to reflect fast changing consumer lifestyles and trends; it enables the consumer to experience brands in his or her everyday life, and it conveys the overall image of the brand by considering the consumer's multi-sensual experiences. The study processed with theoretical research which is related to the hotel space and branded environment. Four brands were selected with distinct business area and brand strategy, and studied to analyze the strategy and the characteristics of the branded environment in a branded hotel. In particular, the case study attempted to evaluate the distinctiveness of the branded hotel's spatial design by comparing each brand's representative flagship store with the hotel. As a result, four characteristics of branded environments in branded hotels were identified, namely, strengthen brand image, consistent brand strategy, extend brand perception, spatialize brand experience. Armani emphasizes their consistent brand image by applying similar design methods in both retail stores and hotel spaces. IKEA, in contrast, applies not their design identity but their brand concepts like practicality, efficiency, and low prices. Pantone gives an expanded brand experience by using synesthetic sensual stimulation using their color system. Missoni mixes and composes their patterns and materials in a three-dimensional manner and strengthens design possibilities and spatiality. This study suggests specific design methods to construct a branded environment in a branded hotel and offers new strategic directions for space branding.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.49-57
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• 2012

Conventional fuzzy c-means (FCM) algorithms have achieved a good clustering performance. However, they do not fully utilize the spatial information in the image and this results in lower clustering performance for images that have low contrast, vague boundaries, and noises. To overcome this issue, we propose an enhanced spatial fuzzy c-means (ESFCM) algorithm that takes into account the influence of neighboring pixels on the center pixel by assigning weights to the neighbors in a $3{\times}3$ square window. To evaluate between the proposed ESFCM and various FCM based segmentation algorithms, we utilized clustering validity functions such as partition coefficient ($V_{pc}$), partition entropy ($V_{pe}$), and Xie-Bdni function ($V_{xb}$). Experimental results show that the proposed ESFCM outperforms other FCM based algorithms in terms of clustering validity functions.

• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.517-534
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• 2019

In abrupt fire disturbances, high quality images suitable for wildfire damage assessment can be difficult to acquire. Quantifying wildfire burn area and severity are essential measures for quick short-term disaster response and efficient long-term disaster restoration. Planetscope (PS) imagery offers 3 m spatial and daily temporal resolution, which can overcome the spatio-temporal resolution tradeoff of conventional satellites, albeit at the cost of spectral resolution. This study investigated the potential of augmenting PS imagery by integrating the spectral information from Sentinel-2 (S2) differenced Normalized Burn Ratio (dNBR) to PS differenced Normalized Difference Vegetation Index (dNDVI) using histogram matching,specifically for wildfire burn area and severity assessment of the Okgye wildfire which occurred on April 4th, 2019. Due to the difficulty in acquiring reference data, the results of the study were compared to the wildfire burn area reported by Ministry of the Interior and Safety. The burn area estimates from this study demonstrated that the histogram-matched (HM) PS dNDVI image produced more accurate burn area estimates and more descriptive burn severity intervals in contrast to conventional methods using S2. The HM PS dNDVI image returned an error of only 0.691% whereas the S2 dNDVI and dNBR images overestimated the wildfire burn area by 5.32% and 106%, respectively. These improvements using PS were largely due to the higher spatial resolution, allowing for the detection of sparsely distributed patches of land and narrow roads, which were indistinguishable using S2 dNBR. In addition, the integration of spectral information from S2 in the PS image resolved saturation effects in areas of low and high burn severity.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.101-108
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• 2024

AI-OCR (Artificial Intelligence Optical Character Recognition) combines OCR technology with Artificial Intelligence to overcome limitations that required human intervention. To enhance the performance of AI-OCR, training on diverse data sets is essential. However, the recognition rate declines when image colors have similar brightness levels. To solve this issue, this study employs Homomorphic filtering as a preprocessing step to clearly differentiate color levels, thereby increasing text recognition rates. While Homomorphic filtering is ideal for text extraction because of its ability to adjust the high and low frequency components of an image separately using a gamma value, it has the downside of requiring manual adjustments to the gamma value. This research proposes a range for gamma threshold values based on tests involving image contrast, brightness, and entropy. Experimental results using the proposed range of gamma values in Homomorphic filtering suggest a high likelihood for effective AI-OCR performance.

• The Journal of the Acoustical Society of Korea
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• v.27 no.2
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• pp.57-65
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• 2008

Setting parameters of Ultrasonic scanners influence the quality of ultrasonic images. In order to obtain optimized images sonographers need to understand the effects of the setting parameters on ultrasonic images. The present study considered typical four parameters including TGC (Time Gain Control), Gain, Frequency, DR (Dynamic Range). LCS (low contrast sensitivity) was chosen to quantitatively compare the quality of the images. In the present experiment LCS targets of a standard ultrasonic test phantom (539, ATS, USA) were imaged using a clinical ultrasonic scanner (SA-9000 PRIME, Medison, Korea). Altering the settings in the parameters of the ultrasonic scanner, 6 LCS target images (+15 dB, +6 dB, +3 dB, -3 dB, -6 dB, -15 dB) to each setting were obtained, and their LCS values were calculated. The results show that the mean pixel value (LCS) is the highest at the max setting in TGC, mid to max in gain and pen mode in frequency and 40-66 dB in DR. Among all images, the image being the highest in LCS was obtained at the setting of DR 40 dB. It is expected that the results will be of use in setting the parameters when ultrasonically examining masses often clinically found In either solid lesions (similar to +15, +6, +3 dB targets) or cystic lesions (similar to -15, -6, -3 dB targets).

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.8
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• pp.62-71
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• 2001

This paper presents a design of the real-time digital image enhancement preprocessor for CMOS image sensor. CMOS image sensor offers various advantages while it provides lower-quality images than CCD does. In order to compensate for the physical limitation of CMOS sensor, the spatially adaptive contrast enhancement algorithm was incorporated into the preprocessor with color interpolation, gamma correction, and automatic exposure control. The efficient hardware architecture for the preprocessor is proposed and was simulated in VHDL. It is composed of about 19K logic gates, which is suitable for low-cost one-chip PC camera. The test system was implemented on Altera Flex EPF10KGC503-3 FPGA chip in real-time mode, and performed successfully.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.275-283
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• 2013

The patient radiation dose is different depending on selection of Ion chamber when taking Chest PA which using AEC. In this paper, we studied acquiring the best diagnostic images according to selection of Ion chamber on AEC mode as well as minimizing patient radiation dose. Experimental methods were selection of Ion chamber and change of sensitivity under the same conditions as Chest PA projection. At AEC mode, two upper ion chambers sensors and one lower ion chamber sensor were divided into 7 cases according to selection of on/off. after measuring five times respectively, we obtained average value and calculated exposure dose. Image assessment was done with measured Modulation Transfer Function, Peak Signal to Noise Ratio, Root Mean Square, Signal to Noise Ratio, Contrast to Noise Ratio, Mean to Standard deviation Ratio respectively. In exposure assessment results, selection of two upper chambers was the lowest. In resolution assessment results, image of two upper chambers had the second high spatial frequency at sensitivity at 625(High) was 1.343 lp/mm. RMS value of image selecting two upper chambers was low secondly. SNR, CNR, MSR were the high value secondly. As the sensitivity was increased, radiation dose was decreased but better image could be obtained on image quality. In order to obtain the best medical images while minimizing the dose, usage of two upper ion chambers is considered to be clinically useful at sensitivity 625(High).

• Korean Journal of Radiology
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• v.21 no.10
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• pp.1165-1177
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• 2020

Objective: To assess the feasibility of applying a deep learning-based denoising technique to coronary CT angiography (CCTA) along with iterative reconstruction for additional noise reduction. Materials and Methods: We retrospectively enrolled 82 consecutive patients (male:female = 60:22; mean age, 67.0 ± 10.8 years) who had undergone both CCTA and invasive coronary artery angiography from March 2017 to June 2018. All included patients underwent CCTA with iterative reconstruction (ADMIRE level 3, Siemens Healthineers). We developed a deep learning based denoising technique (ClariCT.AI, ClariPI), which was based on a modified U-net type convolutional neural net model designed to predict the possible occurrence of low-dose noise in the originals. Denoised images were obtained by subtracting the predicted noise from the originals. Image noise, CT attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were objectively calculated. The edge rise distance (ERD) was measured as an indicator of image sharpness. Two blinded readers subjectively graded the image quality using a 5-point scale. Diagnostic performance of the CCTA was evaluated based on the presence or absence of significant stenosis (≥ 50% lumen reduction). Results: Objective image qualities (original vs. denoised: image noise, 67.22 ± 25.74 vs. 52.64 ± 27.40; SNR [left main], 21.91 ± 6.38 vs. 30.35 ± 10.46; CNR [left main], 23.24 ± 6.52 vs. 31.93 ± 10.72; all p < 0.001) and subjective image quality (2.45 ± 0.62 vs. 3.65 ± 0.60, p < 0.001) improved significantly in the denoised images. The average ERDs of the denoised images were significantly smaller than those of originals (0.98 ± 0.08 vs. 0.09 ± 0.08, p < 0.001). With regard to diagnostic accuracy, no significant differences were observed among paired comparisons. Conclusion: Application of the deep learning technique along with iterative reconstruction can enhance the noise reduction performance with a significant improvement in objective and subjective image qualities of CCTA images.

• Journal of Radiation Protection and Research
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• v.35 no.4
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• pp.135-141
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• 2010

Purpose : The patients who visited this department for pulmonary disease and need CT scans for Follow-up to observe change of CT value, evaluation of image quality and decrease of radiation dose as change of kVp. Subjects and Methods : Subjects were the patients of 20 persons visited this department for pulmonary disease and Somatom Sensation 16(Semens, Enlarge, Germany) was used. Measurement of CT value as change of kVp was done by setting up ROI diameter of 1cm at the height of thyroid, aortic arch, right pulmonary artery in arterial phase image using 100 kVp, measuring 3 times, and recorded the average. CT value of phantom was measured by scanning phantoms which means contrast media diluted by normal saline by various ratio with tube voltage of 80 kVp, 100 kVp, 120 kVp, 140 kVp and recorded the average of 3 CT values of center of phantom image. In analysing radiation dose, CTDIVOL values of the latest arterial phase image of 120 kVp and as this research set that of 100 kVp were analyzed comparatively. 2 observers graded quality of chest images by 5 degrees (Unacceptable, Suboptimal, Adequate, Good, Excellent). Results : CT value of chest image increased at 100 kVp by 14.06%~27.26% in each ROI than 120 kVp. CT value of phantom increased as tube voltage lowered at various concentration of contrast media. CTDIVOL decreased at 100 kVp(5.00 mGy) by 36% than 120 kVp(7.80 mGy) in radiation dose analysis. here were 0 Unacceptable, 1 Suboptimal, 3 Adequate, 10 Good, 6 Excellent in totally 20 persons. Conclusion : Chest CT scanning with low kilo-voltage for patients who need CT scan repeatedly can bring images valuable for diagnose, and decrease radiation dose against patients.