• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.939-944
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• 2002

In this paper, we propose and apply new classification method to the remotely sensed image acquired from airborne multi-spectral scanner. This is a neuro-fuzzy image classifier derived from the generic model of a 3-layer fuzzy perceptron. We implement a classification software system with the proposed method for land cover image classification. Comparisons with the proposed and maximum-likelihood classifiers are also presented. The results show that the neuro-fuzzy classification method classifies more accurately than the maximum likelihood method. In comparing the maximum-likelihood classification map with the neuro-fuzzy classification map, it is apparent that there is more different as amount as 7.96% in the overall accuracy. Most of the differences are in the "Building" and "Pine tree", for which the neuro-fuzzy classifier was considerably more accurate. However, the "Bare soil" is classified more correctly with the maximum-likelihood classifier rather than the neuro-fuzzy classifier.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.439-442
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• 1999

It is important to analyze the seasonal change profiles of land cover type in large scale for establishing preservation strategy and environmental monitoring. Because the NOAA-AVHRR data sets provide global data with high temporal resolution, it is suitable for the land cover classification of the large area. The objectives of this study were to classify land cover of Korea, to investigate the phenological profiles of land cover. The NOAA-AVHRR data from Jan. 1998 to Dec. 1998 were received by Korea Ocean Research & Development Institute(KORDI) and were used for this study. The NDVI data were produced from this data. And monthly maximum value composite data were made for reducing cloud effect and temporal classification. And the data were classified using the method of supervised classification. To label the land cover classes, they were classified again using generalized vegetation map and Landsat-TM classified image. And the profiles of each class was analyzed according to each month. Results of this study can be summarized as follows. First, it was verified that the use of vegetation map and TM classified map was available to obtain the temporal class labeling with NOAA-AVHRR. Second, phenological characteristics of plant communities of Korea using NOAA-AVHRR was identified. Third, NDVI of North Korea is lower on Summer than that of South Korea. And finally, Forest cover is higher than another cover types. Broadleaf forest is highest on may. Outline of covertype profiles was investigated.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.1
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• pp.13-19
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• 2020

This study compared RGB color images with canopy light interception (LI) and leaf area index (LAI) measurements for low cost and low labor. LAI and LI were measured from vertical gap fraction derived from top of digital image in soybean canopy cover (cv Daewonkong, Deapongkong and Pungsannamulkong). RGB color images, LAI, and LI were collected from V4.5 stage to R5stage. Image segmentation was based on excess green minus excess red index (ExG-ExR). There was a linear relationship between LAI measured with LI (r²=0.84). There was alinear relation ship between LI measured with canopy cover on image (CCI) (r²=0.94). There was a significant positive relationship(r²=0.74) between LAI and CCI at all grow ingseason. Therefore, it is expected that in the future, the RGB color image could be able to easily measure the LAI and the LI at low cost and low labor.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.435-444
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• 2011

The land cover map derived from spectral features of high resolution optical images has low spectral resolution and heterogeneity in the same land cover class. For this reason, despite the same land cover class, the land cover can be classified into various land cover classes especially in vegetation area. In order to overcome these problems, detailed vegetation classification is applied to optical satellite image and SAR(Synthetic Aperture Radar) integrated data in vegetation area which is the result of pre-classification from optical image. The pre-classification and vegetation classification were performed with MLC(Maximum Likelihood Classification) method. The hierarchical land cover classification was proposed from fusion of detailed vegetation classes and non-vegetation classes of pre-classification. We can verify the facts that the proposed method has higher accuracy than not only general SAR data and GLCM(Gray Level Co-occurrence Matrix) texture integrated methods but also hierarchical GLCM integrated method. Especially the proposed method has high accuracy with respect to both vegetation and non-vegetation classification.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.71-74
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• 2003

The purpose of this study is to extract agriculture-related information from high-resolution satellite imageries. Calendar of cropping pattern for crops detected on the image was diagrammed, and field investigation was done to check crop status, agricultural facilities and structures. As a result, high-resolution agricultural land cover map from IKONOS imageries was made out.

• Journal of Korea Multimedia Society
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• v.22 no.5
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• pp.527-534
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• 2019

Recently, Photo editing softwares such as digital cameras, Paintshop Pro, and Photoshop digital can create counterfeit images easily. Various techniques for detection of tamper images or forgery images have been proposed in the literature. A form of digital forgery is copy-move image forgery. Copy-move is one of the forgeries and is used wherever you need to cover a part of the image to add or remove information. Copy-move image forgery refers to copying a specific area of an image itself and pasting it into another area of the same image. The purpose of copy-move image forgery detection is to detect the same or very similar region image within the original image. In this paper, we proposed fast detection of forgery image using four step search based on discrete cosine transform and a four step search algorithm using discrete cosine transform (FSSDCT). The computational complexity of our algorithm reduced 34.23 % than conventional DCT three step search algorithm (DCTTSS).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.183-194
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• 2004

We propose a now watermarking scheme that can be used to embed multiple bits and also resilient to geometrical transforms such as scaling, rotation, and cropping, based on off - axis holographic watermark that allows multiple watermark recovery without original content(cover image). The holographic watermark is that Fourier transformed digital hologram is embedded into cover image in the spatial domain. The proposed method has not only increased robustness with a stronger embedding but also imprescriptibility of the watermark in the evaluation process. To compare with the convention기 scheme, the spread spectrum, we embedded and recovered maximum 1,024 bits that consist of binary number over PSNR(peak signal-to-noise ratio) 39dB. And also, we computed robustness with BER(bit error rate) corresponding the above attack

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.1
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• pp.1-10
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• 2017

An UAV (Unmanned Aerial Vehicle) is a flight system that is designed to conduct missions without a pilot. Compared to traditional airborne-based photogrammetry, UAV-based photogrammetry is inexpensive and can obtain high-spatial resolution data quickly. In this study, we aimed to classify the land cover using high-spatial resolution images obtained using a UAV. An RGB camera was used to obtain high-spatial resolution orthoimage. For accurate classification, multispectral image about same areas were obtained using a multispectral sensor. A DSM (Digital Surface Model) and a modified NDVI (Normalized Difference Vegetation Index) were generated using images obtained using the RGB camera and multispectral sensor. Pixel-based classification was performed for twelve classes by using the RF (Random Forest) method. The classification accuracy was evaluated based on the error matrix, and it was confirmed that the proposed method effectively classified the area compared to supervised classification using only the RGB image.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.2
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• pp.51-76
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• 2009

In this paper, a new hybrid opto-digital multiple information hiding and real-time extracting system was suggested and implemented using a volume holographic optical correlator. The multiple information hiding system in which the multiple information can be hided in an arbitrary cover image was digitally implemented by using the combination of pseudo random sequence and Hadamard matrix. In addition, a real-time optical extraction system in which the hided multiple information in a cover image can be extracted in real-time was implemented by using a volume holographic optical correlator. In the VanderLugt-type holographic optical correlator used in this experiment, the multiful matched spatial filters corresponding each of the hided informations were recorded in a photorefractive crystal by using the moving window-based angular multiplexing scheme.

• Journal of Multimedia Information System
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• v.1 no.1
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• pp.1-10
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• 2014

In this paper, we propose a new view synthesis technique for coding of multi-view color and depth data in arbitrary camera arrangements. We treat each camera position as a 3-D point in world coordinates and build clusters of those vertices. Color and depth data within a cluster are gathered into one camera position using a hierarchical representation based on the concept of layered depth image (LDI). Since one camera can cover only a limited viewing range, we set multiple reference cameras so that multiple LDIs are generated to cover the whole viewing range. Therefore, we can enhance the visual quality of the reconstructed views from multiple LDIs comparing with that from a single LDI. From experimental results, the proposed scheme shows better coding performance under arbitrary camera configurations in terms of PSNR and subjective visual quality.