• Journal of Radiation Industry
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• v.17 no.4
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• pp.397-403
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• 2023

The purpose of this study is to obtain brain MRI images through Heavenly T₂ FLAIR and DWI techniques to find out strengths and weaknesses of each image. Data were analyzed on 13 normal people and 17 brain tumor patients. Philips Ingenia 3.0TCX was used as the equipment used for the inspection, and 32 Channel Head Coil was used to acquire data. Using Image J and Infinity PACS Data, 3mm² of gray matter, white matter, cerebellum, basal ganglia, and tumor areas were set and measured. Quantitative analysis measured SNR and CNR as an analysis method, and qualitative analysis evaluated overall image quality, lesion conspicuity, image distortion, susceptibility artifact and ghost artifact on a 5-point scale. The statistical significance of data analysis was that Wilcox-on Signed Rank Test and Paired t-test were executed, and the statistical program used was SPSS ver.22.0 and the p value was less than 0.05. In quantitative analysis, the SNR of gray matter, white matter, cerebellum, basal ganglia, and tumor of Heavily T₂ FLAIR is 41.45±0.13, 40.52±0.45, 41.44±0.51, 40.96±0.09, 35.28±0.46 and the CNR is 15.24±0.13, 16.75±0.23, 16.28±0.41, 15.83±0.17, 16.63±0.51. In DWI, SNR is 32.58±0.22, 36.75±0.17, 30.21±0.19, 35.83±0.11, 43.29±0.08, and CNR is 13.14±0.63, 14.21±0.31, 12.95±0.32, 11.73±0.09, 17.56±0.52. In normal tissues, Heavenly T₂ FLAIR obtained high results, but in disease evaluation, high results were obtained at DWI, b=1000 (p<0.05). In addition, in the qualitative analysis, overall image quality, lesion conspicuity, image distortion, susceptibility artifact and ghost artifact aspects of the Heavily T₂ FLAIR were evaluated, and 3.75±0.28, 2.29±0.24, 3.86±0.23, 4.08±0.21, 3.79±0.22 values were found, respectively, and 2.53±0.39, 4.13±0.29, 1.90±0.20, 1.81±0.21, 1.52±0.45 in DWI. As a result of qualitative analysis, overall image quality, image distortion, susceptibility artifact and ghost artifact were rated higher than DWI. However, DWI was evaluated higher in lesion conspicuity (p<0.05). In normal tissues, the level of Heavenly T₂ FLAIR was higher, but the DWI technique was higher in the evaluation of the disease (tumor). The two results were necessary techniques depending on the normal site and the location of the disease. In conclusion, statistically significant results were obtained from the two techniques. In quantitative and qualitative analysis, the two techniques had advantages and disadvantages, and in normal and disease evaluation, the two techniques produced useful results. These results are believed to be educational data for clinical basic evaluation and MRI in the future.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.453-456
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• 2003

Compared with other features of the image, color features are less sensitive to noise and background complication. Besides, this adding to object segmentation has more accuracy of image retrieval. This paper presents object segmentation and HAQ(Histogram Analysis and Quantization) algorithm approach to extract features(the object information and the characteristic colors) of an image. The empirical results shows that this method presents exactly spatial and color information of an image as image retrieval's feature.

• Archives of design research
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• v.15 no.4
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• pp.399-408
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• 2002

According to the improvement in quality of life and the progress of user's taste in this modern society, people great deal with the symbolic meaning of product which express user's self-concept(image). Therefore, this kind of information of users' image is needed to deal importantly for the product design development processes, particularly, the early stage of design development such as the concept design development stage. But, there is not much analysis tools which deal qualitative data of users for the design development. From this reason, the supply of information of user's image through the development of verbal analysis method of user's self-concept will help a designer. For this purpose, this study not only developed the twenty-one factors in order to evaluate user's self-concept, but also suggested that the new approach method that can classify user's group within the same characteristic of user's image using the twenty-one developed verbal measurement items with tools of statistical analysis for the design direction of product. The developed this verbal analysis tool was testified through the case study in this research work.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3268-3283
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• 2018

With the advent of the Information Age, the source identification of digital images, as a part of digital image forensics, has attracted increasing attention. Therefore, an effective technique to identify the source of digital images is urgently needed at this stage. In this paper, first, we study and implement some previous work on image source identification based on sensor pattern noise, such as the Lukas method, principal component analysis method and the random subspace method. Second, to extract a purer sensor pattern noise, we propose a sample selection method to improve the random subspace method. By analyzing the image texture feature, we select a patch with less complexity to extract more reliable sensor pattern noise, which improves the accuracy of identification. Finally, experiment results reveal that the proposed sample selection method can extract a purer sensor pattern noise, which further improves the accuracy of image source identification. At the same time, this approach is less complicated than the deep learning models and is close to the most advanced performance.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.35 no.4
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• pp.23-33
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• 2003

The possibility of real time analysis about hot melt resins and pressure sensitive adhesives in newsprint stock was investigated by performing comparative tests using conventional image analysis method and real time contaminants analyzer. Based on the test results, the performance of real time contaminants analyzer in terms of detecting primary stickies in newsprint stock could be verified. Real time stickies analysis showed good precision and over-estimation of hot melt resins and under-estimation of pressure sensitive adhesives could be corrected by adapting new method. Real time analysis of primary stickies in the actual newsprint stock also showed good correlation with conventional image analysis and the performance of real time contaminants analyzer could be verified again. Adjustment of the contrast sensitivity of real time contaminants analyzer was enough to set the proper monitoring conditions for primary stickies in newsprint stock.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.727-731
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• 2003

ASTER image has some advantages for classification such as 15 spectral bands and 15m ${\sim}$ 90m spatial resolution. However, in the classification using general remote sensing image, shadow areas are often classified into water area. It is very difficult to divide shadow and water. Because reflectance characteristics of water is similar to characteristics of shadow. Many land cover items are consisted in one pixel which is 15m spatial resolution. Nowadays, very high resolution satellite image (IKONOS, Quick Bird) and Digital Surface Model (DSM) by air borne laser scanner can also be used. In this study, mixed pixel analysis of ASTER image has carried out using IKONOS image and DSM. For mixed pixel analysis, high accurated geometric correction was required. Image matching method was applied for generating GCP datasets. IKONOS image was rectified by affine transform. After that, one pixel in ASTER image should be compared with corresponded 15×15 pixel in IKONOS image. Then, training dataset were generated for mixed pixel analysis using visual interpretation of IKONOS image. Finally, classification will be carried out based on Linear Mixture Model. Shadow extraction might be succeeded by the classification. The extracted shadow area was validated using shadow image which generated from 1m${\sim}$2m spatial resolution DSM. The result showed 17.2% error was occurred in mixed pixel. It might be limitation of ASTER image for shadow extraction because of 8bit quantization data.

• Journal of the Korean Society for Advanced Composite Structures
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• v.6 no.3
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• pp.20-25
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• 2015

This paper introduces a digital image processing(DIP) method as a method for measuring the displacement of pylon. The comparison of DIP results and ANSYS analysis results verified the validity of the image processing technique. Normalized cross-correlation(NCC) coefficient was used and experiments were performed three times. It shows that the displacement difference was 22% and 5% compared to ANSYS results. Therefore, the image processing method is expected to be able to measure the displacement of pylon sufficiently.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.2
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• pp.130-135
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• 2016

Gait recognition has advantage of non-contact type recognition. But It has disadvantage of low recognition rate when the pedestrian silhouette is changed due to bag or coat. In this paper, we proposed new method using combination of gait energy image feature and thermal face image feature. First, we extracted a face image which has optimal focusing value using human body rate and Tenengrad algorithm. Second step, we extracted features from gait energy image and thermal face image using linear discriminant analysis. Third, calculate euclidean distance between train data and test data, and optimize weights using genetic algorithm. Finally, we compute classification using nearest neighbor classification algorithm. So the proposed method shows a better result than the conventional method.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.952-954
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• 2005

The objective of this paper is to propose the image interpolation method with pseudomedian filter for Field warping and morphing, and to evaluate and analyze its subjective image quality. The Field warping relatively gives rise to more computing overhead, but it can use the control line to control the warping result with more elaboration. Due to the working characteristics of the image warping and morphing process, various complex geometrical transformations occur and a image interpolation technique is needed to effectively process them. Of the various interpolation techniques, bilinear interpolation which shows above average performance is the most widely used. However, this technology has its limits in the reconstructivity of diagonal edges. The proposed interpolation method is to efficiently combine the bilinear interpolation and the pseudomedian filter0based interpolation which shows good performance in the reconstructivity of diagonal edges. According to the proposed interpolation method, we could get more natural warping and morphing results than other interpolation methods.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.11
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• pp.634-643
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• 2003

This paper presents a method for detecting skin tumors on chicken carcasses using hyperspectral images. It utilizes both fluorescence and reflectance image information in hyperspectral images. A detection system that is built on this concept can increase detection rate and reduce processing time, because the procedure for detection can be simplified. Chicken carcasses are examined first using band ratio FCM information of fluorescence image and it results in candidate regions for skin tumor. Next classifier selects the real tumor spots using PCA components information of reflectance image from the candidate regions. For the real world application, real-time processing is a key issue in implementation and the proposed method can accommodate the requirement by using a limited number of features to maintain the low computational complexity. Nevertheless, it shows favorable results and, in addition, uncovers meaningful spectral bands for detecting tumors using hyperspectral image. The method and findings can be employed in implementing customized chicken tumor detection systems.