• 한국멀티미디어학회논문지
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• 제20권2호
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• pp.163-169
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• 2017

There are various algorithms evaluating a threshold for image segmentation. Among them, Otsu's algorithm sets a threshold based on the histogram. It finds the between-class variance for all over gray levels and then sets the largest one as Otsu's optimal threshold, so we can see that Otsu's algorithm requires a lot of the computation. In this paper, we improved the amount of computational needs by using estimated Otsu's threshold rather than computing for all the threshold candidates. The proposed algorithm is compared with the original one in computation amount and accuracy. we confirm that the proposed algorithm is about 29 times faster than conventional method on single processor and about 4 times faster than on parallel processing architecture machine.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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• pp.218-224
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• 1998

The coefficients of variation obtained from three typical vegetation indices of eight levels of multi-spatial resolution images in urban areas were employed to identify the optimum spatial resolution in terms of maintaining information quality. These multi-spatial resolution images were prepared by degrading 1 meter simulated, 16 meter ADEOS/AVNIR, and 30 meter Landsat-TM images. Normalized Difference Vegetation Index (NDVI), Perpendicular Vegetation Index (PVI) and Soil Adjusted Ratio Vegetation Index (SARVI) were applied to reduce data redundancy and compare the characteristics of multi-spatial resolution image of vegetation indices. The threshold point on the curve of the coefficient of variation was defined as the optimum resolution level for the analysis with multi-spatial resolution image sets. Also, the results from the image segmentation approach of region growing to extract man-made features were compared with these multi-spatial resolution image sets.

• Communications for Statistical Applications and Methods
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• 제29권2호
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• pp.161-176
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• 2022

There has been active research in image classification using deep learning convolutional neural network (CNN) models. ImageNet large-scale visual recognition challenge (ILSVRC) (2010-2017) was one of the most important competitions that boosted the development of efficient deep learning algorithms. This paper introduces and compares six monumental models that achieved high prediction accuracy in ILSVRC. First, we provide a review of the models to illustrate their unique structure and characteristics of the models. We then compare those models under a unified framework. For this reason, additional devices that are not crucial to the structure are excluded. Four popular data sets with different characteristics are then considered to measure the prediction accuracy. By investigating the characteristics of the data sets and the models being compared, we provide some insight into the architectural features of the models.

• 한국유통학회지:유통연구
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• 제12권2호
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• pp.79-102
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• 2007

점포의 평가는 소비자의 마음속에 자리 잡고 있는 유사한 경쟁점포들 내에서 이루어지게 되며, 이렇게 "소비자가 특정 점포선택을 할 때 실제 고려하게 되는 점포들의 집합"을 고려점포군(考廬店鋪群; consideration set of stores)이라 한다. 본 연구에서는 소비자가 의류제품을 구매할 때 점포선택과정 중에 형성하는 고려점포군을 알아보고, 고려점포군과 점포이미지 중요도와의 관련성을 알아보고자 하였다. 연구결과에서 의류점포선택과정을 통해 형성된 고려점포군은 결과적으로 고려점포수와 고려하는 점포유형에 따라 다시 구체화될 수 있으며, 이를 기준으로 소비자 유형화를 실시한 결과 '소수-가두점 고려집단', '소수-시장 고려집단', '소수-백화점 고려집단', '소수-백화점/아울렛 고려집단', '다수-백화점/시장 고려집단', '다수-백화점/가두점 고려집단', '다수-백화점 고려집단'으로 구분되었으며, 유형화된 소비자 집단별 점포이미지 중요도에 있어서 유의한 차이가 있음이 밝혀졌다. 예를 들면, 시장을 고려점포유형으로 포함하는 소수-시장 고려집단과 다수-백화점/시장 고려집단은 저렴한 가격을 중요한 점포이미지로 여겼으며, 소수-백화점 고려집단은 점포 마일리지 카드나 할인카드, 다수-백화점/가두점 고려집단은 주변 여가공간 요인을 중요한 점포이미지로 꼽아 집단별 차이를 나타냈다. 이러한 결과들은 점포 운영자들이 자사 목표고객과 경쟁점포를 파악하고 이에 대응한 마케팅 전략을 수립하는데 효과적으로 사용될 수 있을 것으로 생각된다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.314-319
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• 1998

In this paper, for efficient data classification in multispectral bands environment, a band feature extraction method using the Rough sets theroy is proposed. First, we make a look up table from training data, and analyze the properties of experimental multispectral image data, then select the efficient band usin indiscernibility relation of Rough sets theory from analysis results. Proposed method is applied to LAMDSAT TM data on 2, June, 1992. Among them, normal distributive data were experimented, mainly. From this, we show clustering trends that similar to traditional band selection results by wavelength properties, from this, we verify that can use the proposed method that centered on data properties to select the efficient bands, though data sensing environment change to hyperspectral band environments.

• Journal of Advanced Marine Engineering and Technology
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• 제34권3호
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• pp.407-412
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• 2010

According to the remarkable advances in sonar technology, positioning capabilities and computer processing power we can accurately image and explore the seafloor in hydrography. Especially, Multibeam Echo Sounder can provide nearly perfect coverage of the seafloor with high resolution. Since the mid-1990's, Multibeam Echo Sounders have been used for hydrographic surveying in Korea. In this study, new marine data set as an effective decision-making tool in various fields was proposed by visualizing and combining with Multibeam sonar data and marine spatial data sets such as satellite image and digital nautical chart. The proposed method was tested around the port of PyeongTaek-DangJin in the west coast of Korea. The Visualization and fusion methods are described with various marine data sets with processing. We demonstrated that new data set in marine GIS is useful in safe navigation and port management as an efficient decision-making tool.

• 대한수학회논문집
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• 제28권1호
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• pp.11-24
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• 2013

The notion of intersectional soft sets is introduced, and several examples are given. The application of intersectional soft sets to BCK/BCI-algebras is discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권12호
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• pp.5087-5102
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• 2015

Rapid popularization of smart cell phone equipped with camera has led to a number of new legal and criminal problems related to multimedia such as digital image, which makes cell phone source identification an important branch of digital image forensics. This paper proposes a classifier combination based source identification strategy for cell phone images. To identify the outlier cell phone models of the training sets in multi-class classifier, a one-class classifier is orderly used in the framework. Feature vectors including color filter array (CFA) interpolation coefficients estimation and multi-feature fusion is employed to verify the effectiveness of the classifier combination strategy. Experimental results demonstrate that for different feature sets, our method presents high accuracy of source identification both for the cell phone in the training sets and the outliers.

• 제어로봇시스템학회논문지
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• 제16권7호
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• pp.695-702
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• 2010

This paper presents an image alignment algorithm for application of AOI (Automatic Optical Inspection) based on SIFT. Since the correspondences result using SIFT descriptor have many wrong points for aligning, this paper modified and classified those points by five measures called the CCFMR (Cascade Classifier for False Matching Reduction) After reduced the false matching, rotation and translation are estimated by point selection method. Experimental results show that the proposed method has fewer fail matching in comparison to commercial software MIL 8.0, and specially, less than twice with the well-controlled environment’s data sets (such as AOI system). The rotation and translation accuracy is robust than MIL in the noise data sets, but the errors are higher than in a rotation variation data sets although that also meaningful result in the practical system. In addition to, the computational time consumed by the proposed method is four times shorter than that by MIL which increases linearly according to noise.

• Architectural research
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• 제12권2호
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• pp.53-62
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• 2010

The purpose of this study is to examine design preferences for the sales spaces of duty-free shops (DFSs) by conducting image evaluations. The results will help improve quality by influencing designs for the construction, extension or remodeling of these shops. An image measurement method, the semantic differential method, was used to measure cognitive structure using photos of shops. Photos were collected of the DFS at Jeju Island, as well as photos of brand stores designed by architects. Two sets of 16 photos (32 different photos in all) were selected according to photo classification standards and design concepts, both decided by reviewing previous studies and related materials. The evaluation and survey were done by two sets of subjects: sales employees, who have experience and special knowledge of the evaluation of sales space; and students majoring in architecture. To strengthen the evaluation results, I conducted a preliminary survey and a main survey, verifying and complementing findings. 116 surveys were conducted, of which 14 were of poor quality and rejected, leaving and 102 to be analyzed. The collected surveys were statistically analyzed, using SPSS 12.0 for Windows. Reliability, image profile, factor and multi-dimensional scaling analyses were conducted. As a result, image evaluation structure and characteristics were obtained for sales spaces of DFSs, confirming the difference between them and other spaces.