• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.611-619
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• 2013

Although the need of crop production has increased in Mongolia, crop cultivation is very limited because of the harsh climatic and topographic conditions. Crop lands are sparsely distributed with relatively small sizes and, therefore, it is difficult to survey the exact area of crop lands. The study aimed to find an easy and effective way of accurate classification to map crop lands in Mongolia using satellite images. To classify the crop lands over the study area in northern Mongolia, four classifications were carried out by using 1) Thematic Mapper (TM) image August 23, 2) TM image of July 6, 3) combined 12 bands of TM images of July and August, and 4) both TM images of July and August by layered classification. Wheat and potato are the major crop types and they show relatively high variation in crop conditions between July and August. On the other hands, other land cover types (forest, riparian vegetation, grassland, water and bare soil) do not show such difference between July and August. The results of four classifications clearly show that the use of multi-temporal images is essential to accurately classify the crop lands. The layered classification method, in which each class is separated by a subset of TM images, shows the highest classification accuracy (93.7%) of the crop lands. The classification accuracies are lower when we use only a single TM image of either July or August. Because of the different planting practice of potato and the growth condition of wheat, the spectral characteristics of potato and wheat cannot be fully separated from other cover types with TM image of either July or August. Further refinements on the spatial characteristics of existing crop lands may enhance the crop mapping method in Mongolia.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.3
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• pp.277-282
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• 2018

The goal of the secret message communication on the internet is to maintain invisibility and confidentiality. Digital steganography is a technique in which a secret message is inserted in a cover medium and transmitted to a destination so that a third party can not perceive the existence of the message itself. Steganography is an efficient method for ensuring confidentiality and integrity together with encryption techniques. In order to insert a secret (Hangul) message, I propose a image steganography method that the secret character is separated and converted into binary code with reference to the encryption table, the cover image is divided into two areas, and the secret message and the right l-LSB information of the second area are encrypted and crossed, concealing the k-LSB of the first region. The experimental results of the proposed method show that the PSNR value is 52.62 and the acceptable image quality level.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.71-77
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• 2006

Support Vector Machine (SVM) which has roots in a statistical learning theory is a training algorithm based on structural risk minimization. Generally, SVM algorithm uses the kernel for determining a linearly non-separable boundary and classifying the data. But, classical kernels can not apply to effectively the hyperspectral image classification because it measures similarity using vector's dot-product or euclidian distance. So, This paper proposes the spectral similarity kernel to solve this problem. The spectral similariy kernel that calculate both vector's euclidian and angle distance is a local kernel, it can effectively consider a reflectance property of hyperspectral image. For validating our algorithm, SVM which used polynomial kernel, RBF kernel and proposed kernel was applied to land cover classification in Hyperion image. It appears that SVM classifier using spectral similarity kernel has the most outstanding result in qualitative and spatial estimation.

• International Journal of Knowledge Content Development & Technology
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• v.7 no.1
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• pp.57-78
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• 2017

There are several statistical classification algorithms available for land use/land cover classification. However, each has a certain bias or compromise. Some methods like the parallel piped approach in supervised classification, cannot classify continuous regions within a feature. On the other hand, while unsupervised classification method takes maximum advantage of spectral variability in an image, the maximally separable clusters in spectral space may not do much for our perception of important classes in a given study area. In this research, the output of an ANN algorithm was compared with the Possibilistic c-Means an improvement of the fuzzy c-Means on both moderate resolutions Landsat8 and a high resolution Formosat 2 images. The Formosat 2 image comes with an 8m spectral resolution on the multispectral data. This multispectral image data was resampled to 10m in order to maintain a uniform ratio of 1:3 against Landsat 8 image. Six classes were chosen for analysis including: Dense forest, eucalyptus, water, grassland, wheat and riverine sand. Using a standard false color composite (FCC), the six features reflected differently in the infrared region with wheat producing the brightest pixel values. Signature collection per class was therefore easily obtained for all classifications. The output of both ANN and FCM, were analyzed separately for accuracy and an error matrix generated to assess the quality and accuracy of the classification algorithms. When you compare the results of the two methods on a per-class-basis, ANN had a crisper output compared to PCM which yielded clusters with pixels especially on the moderate resolution Landsat 8 imagery.

• Journal of radiological science and technology
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• v.44 no.1
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• pp.1-8
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• 2021

The purpose of this study was to analyze the effect of automatic exposure control (AEC) control factors in digital radiography systems based on the fine contrast images using coin phantoms. The AEC control factors were targeted at the range of dominent zone, sensitivity, and density. The dominent zone was divided into cases where a single coin was used to cover the field configuration, and cases where seven coins were used to cover the field configuration. The sensitivity was classified into three stages (200, 400, 800) and the density was classified into three stages (2.5, 0, 2.5). Image quality was evaluated by signal to noise ratio (SNR) and contrast to noise ratio (CNR). Then, the automatically exposed tube current was measured. As a result, the X-ray image of seven coins obtained a result value of about 1.2 times higher for SNR and 1.9 times higher for CNR than the X-ray image for one coin. The tube current was also about 1.6 times higher. In conclusion, In AEC, the higher the field configuration and dominent zone are matched and the higher the density, the lower the sensitivity, which increases the tube current and CNR, which increases the image quality. Therefore, it is judged that the appropriate setting of the range of dominent zone, sensitivity, and density of the control, which is the AEC control factor, could improve the fine contrast of images.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.33-40
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• 2022

With the recent increase in the development of military drones, they are adopted and used as the combat system of battalion level or higher. However, it is difficult to use drones that can be used in battles below the platoon level due to the current conditions for the formation of units in the Korean military. In this paper, therefore, we developed a program drones equipped with a thermal imaging camera and LiDAR sensor for reconnaissance and exploration that can be applied in battles below the platoon level. Using these drones, we studied the possibility and feasibility of drones for small-scale combats that can find hidden enemies, search for an appropriate detour through image processing and conduct reconnaissance and search for battlefields, hiding and cover-up through image processing. In addition to the purpose of using the proposed drone to search for an enemies lying in ambush in the battlefield, it can be used as a function to check the optimal movement path when a combat unit is moving, or as a function to check the optimal place for cover-up or hiding. In particular, it is possible to check another route other than the route recommended by the program because the features of the terrain can be checked from various viewpoints through 3D modeling. We verified the possiblity of flying by designing and assembling in a form of adding LiDAR and thermal imaging camera module to a drone assembled based on racing drone parts, which are open source hardware, and developed autonomous flight and search functions which can be used even by non-professional drone operators based on open source software, and then installed them to verify their feasibility.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2941-2956
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• 2013

In this paper, we propose an effective fragile image watermarking scheme for tampering detection and content recovery. Cover image is divided into a series of non-overlapping blocks and a block mapping relationship is constructed by the secret key. Several DCT coefficients with direct current and lower frequencies of the MSBs for each block are used to generate the reference bits, and different coefficients are assigned with different bit numbers for representation according to their importance. To enhance recovery performance, authentication bits are generated by the MSBs and the reference bits, respectively. After LSB substitution hiding, the embedded watermark bits in each block consist of the information of itself and its mapping blocks. On the receiver side, all blocks with tampered MSBs can be detected and recovered using the valid extracted reference bits. Experimental results demonstrate the effectiveness of the proposed scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.13-16
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• 1999

An active contour model, Snake, was developed as a useful segmenting and tracking tool lot rigid or non-rigid (i.e. deformable) objects by Kass in 1987 In this research, Snake is newly designed to cover this large moving case. Image flow energy is proposed to give Snake the motion information of the target object. By this image flow energy Snake's nodes can move uniformly along the direction of the target motion in spite of the existences of local minima. Furthermore, when the motion is too large to apply image flow energy to tracking, a jump mode is proposed for solving the problem. The vector used to make Snake's nodes jump to the new location can be obtained by processing the image flow. The effectiveness of the proposed Snake is confirmed by some simulations.

• Fashion & Textile Research Journal
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• v.4 no.3
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• pp.284-288
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• 2002

In this research, a new quantitative fabric drape evaluation system has been developed using image processing technology. The purpose of this research is to get the more detailed information of fabric drapability quantitatively from digital images captured with a digital camera generally commercialized. The shape parameters of a 3-dimensional geometric drape model were defined as the number of nodes, frequency and amplitude. Also, various statistical information of drape shapes can be obtained using image processing technology and frequency analysis as well as traditional drape coefficients. Hardware system to capture drape images is simply composed of three parts including a digital USB (Universal Serial Bus) camera, a frame cover and a stand for camera to attach to traditional drape tester. The evaluation software coded with the MS Visual C++ is operated under the MS windows 9x above.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.681-687
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• 2016

Today's modern world requires a digital watermarking technique that takes the redundancy of an image into consideration for embedding a watermark. The novel algorithm used in this paper takes into consideration the redundancies of spatial domain and wavelet domain for embedding a watermark. Also, the cryptography-based secret key makes the algorithm difficult to hack and help protect ownership. Watermarking is blind, as it does not require the original image. Few coefficient matrices and secret keys are essential to retrieve the original watermark, which makes it redundant to various intentional attacks. The proposed technique resolves the challenge of optimizing transparency and robustness using a Canny-based edge detector technique. Improvements in the transparency of the cover image can be seen in the computed PSNR value, which is 44.20 dB.