• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.28 no.1
• /
• pp.133-142
• /
• 2010

To monitor composition and change of the national land, intelligent topographical classifier which enables accurate classification of land-cover types from airborne LiDAR data is highly required. We developed a topographical classifier development support system cooperating with da1a mining tool WEKA to help users to construct accurate topographical classification systems. The topographical classifier development support system has the following functions; superposing LiDAR data upon corresponding aerial images, dividing LiDAR data into tiles for efficient processing, 3D visualization of partial LiDAR data, feature from tiles, automatic WEKA input generation, and automatic C++ program generation from the classification rule set. In addition, with dam mining tool WEKA, we can choose highly distinguishable features by attribute selection function and choose the best classification model as the result topographical classifier. Therefore, users can easily develop intelligent topographical classifier which is well fitted to the developing objectives by using the topographical classifier development support system.

• Journal of the Korean Geosynthetics Society
• /
• v.20 no.4
• /
• pp.63-71
• /
• 2021

Recently, high-resolution cameras in smartphones enable measurement of minute objects such as cracks in concrete using image processing techniques. The technology to investigate the crack width using an application at an adjacent distance of the close shot range has already been implemented, but the use is limited, so it is necessary to verify the usability of the high-resolution smartphone camera to measure cracks at a longer distance. This study focuses on recognizing the size of subdivided crack widths at a thickness within 1.0 mm of crack width at a distance of 2 m. In recent Android-based smartphones, an experiment was conducted focusing on the relationship between the unit pixel size, which is a measurement component, and the shooting distance, depending on the camera resolution. As a result, it was possible to confirm the necessity of a smartphone lens for the classification and quantification of microcrack widths of 0.3 mm to 1mm. The universal telecentric lens for smartphones needed to be installed in an accurate position to minimize the effect of distortion. In addition, as a result of applying a 64 MP high-resolution smartphone camera and double magnification lens, the crack width could be calculated within 2 m in pixel units, and crack widths of 0.3, 0.5, and 1mm could be distinguished.

• The KIPS Transactions:PartD
• /
• v.14D no.4 s.114
• /
• pp.447-458
• /
• 2007

The objective of this study is to provide faster mobile web service by improving performance of Contents Cache used for mobile web service in the existing Mobile Gate System. It was found that two elements existed in Mark-Up page transcoded by Contents Generator. One of the elements was dependent only on the requested DIDL page and Mark-Up type. The other was dependent on each of the requested DIDL page, Mark-Up type, size of mobile display 모바일 장치 to request service, type of images available and color depth count of the images available. The conventional Contents Cache saved the entire Mark-Up page to hold both of the two elements. This caused the problem where storage space was not effectively used because reusable elements were repetitively saved in cache memory domain due to change in one of the elements even though all the other elements were the same. As a result, a larger number of transcoded Mark-Up pages could not be saved in the same cache memory size. Therefore, in this study, Mark-Up pages transcoded by Contents Generator were divided into two elements and were separately saved. Also, in order to respond to the demand for replacing data in cache with new data, this study applied two algorithms of LFU and LRU. This study proposed the method to implement cache performance of faster speed by enabling to save more number of the transcoded Mark-Up pages in the same cache storage space.

• The KIPS Transactions:PartD
• /
• v.8D no.5
• /
• pp.507-512
• /
• 2001

Feature-based similarity has become an important research issue in multimedia database systems. The features of multimedia data are useful for discriminating between multimedia objects. the performance of conventional multidimensional data structures tends to deteriorate as the number of dimensions of feature vectors increase. The $R^{*}-Tree$ is the most successful variant of the R-Tree. In this paper, we propose a SOM-based $R^{*}-Tree$ as a new indexing method for high-dimensional feature vectors. The SOM-based $R^{*}-Tree$ combines SOM and $R^{*}-Tree$ to achieve search performance more scalable to high-dimensionalties. Self-Organizingf Maps (SOMs) provide mapping from high-dimensional feature vectors onto a two-dimensional space. The map is called a topological feature map, and preserves the mutual relationships (similarity) in the feature spaces of input data, clustering mutually similar feature vectors in neighboring nodes. Each node of the topological feature map holds a codebook vector. We experimentally compare the retrieval time cost of a SOM-based $R^{*}-Tree$ with of an SOM and $R^{*}-Tree$ using color feature vectors extracted from 40,000 images. The results show that the SOM-based $R^{*}-Tree$ outperform both the SOM and $R^{*}-Tree$ due to reduction of the number of nodes to build $R^{*}-Tree$ and retrieval time cost.

• Geophysics and Geophysical Exploration
• /
• v.24 no.3
• /
• pp.113-130
• /
• 2021

Recently, ground-penetrating radar (GPR) surveys have been actively employed to obtain a large amount of data on occurrences such as ground subsidence and road safety. However, considering the cost and time efficiency, more intuitive and accurate interpretation methods are required, as interpreting a whole survey data set is a cost-intensive process. For this purpose, GPR data can be subjected to attribute analysis, which allows quantitative interpretation. Among the seismic attributes that have been widely used in the field of exploration, complex trace analysis and similarity are the most suitable methods for analyzing GPR data. Further, recently proposed attributes such as edge detecting and texture attributes are also effective for GPR data analysis because of the advances in image processing. In this paper, as a reference for research on the attribute analysis of GPR data, we introduce the useful attributes for GPR data and describe their concepts. Further, we present an analysis of the interpretation methods based on the attribute analysis and past cases.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.7
• /
• pp.326-334
• /
• 2024

Extra-oral imaging techniques such as Panoramic X-rays (PXs) and Cone Beam Computed Tomography (CBCT) are the most preferred imaging modalities in dental clinics owing to its patient convenience during imaging as well as their ability to visualize entire teeth information. PXs are preferred for routine clinical treatments and CBCTs for complex surgeries and implant treatments. However, PXs are limited by the lack of third dimensional spatial information whereas CBCTs inflict high radiation exposure to patient. When a PX is already available, it is beneficial to reconstruct the 3D oral structure from the PX to avoid further expenses and radiation dose. In this paper, we propose 3DentAI - an U-Net based deep learning framework for 3D reconstruction of oral structure from a PX image. Our framework consists of three module - a reconstruction module based on attention U-Net for estimating depth from a PX image, a realignment module for aligning the predicted flattened volume to the shape of jaw using a predefined focal trough and ray data, and lastly a refinement module based on 3D U-Net for interpolating the missing information to obtain a smooth representation of oral cavity. Synthetic PXs obtained from CBCT by ray tracing and rendering were used to train the networks without the need of paired PX and CBCT datasets. Our method, trained and tested on a diverse datasets of 600 patients, achieved superior performance to GAN-based models even with low computational complexity.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.4
• /
• pp.948-953
• /
• 2015

Recently, the finger vein recognition based on NIR and CCD sensor camera is investigating the technology to identify a personal using by biometrics. The performance difference of finger vein recognition is generated according to methods that are to separate the vein and background from noises such as finger thickness, ambient light, skin temperature, etc. To improve these problems, in this study, we are proposing the methods for rotation, ROI extraction, and enhancement of vein image captured by NIR LED and CCD camera, and were evaluated performances of these methods. In results of the experiment, the accuracy of the proposed method for image rotation and ROI extraction was 99.8%. And the proposed filter bank method in vein enhancement has shown better performance than retinex algorithm. The proposed method for results of these experimentations will provide better recognition rate when applied to the preprocessing of finger vein recognition.

• KIPS Transactions on Software and Data Engineering
• /
• v.7 no.3
• /
• pp.91-98
• /
• 2018

Automatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. In particular, porcine respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this paper, we propose a noise-robust system for the early detection and recognition of pig wasting diseases using sound data. In this method, first we convert one-dimensional sound signals to two-dimensional gray-level images by normalization, and extract texture images by means of dominant neighborhood structure technique. Lastly, the texture features are then used as inputs of convolutional neural networks as an early anomaly detector and a respiratory disease classifier. Our experimental results show that this new method can be used to detect pig wasting diseases both economically (low-cost sound sensor) and accurately (over 96% accuracy) even under noise-environmental conditions, either as a standalone solution or to complement known methods to obtain a more accurate solution.

• The KIPS Transactions:PartB
• /
• v.19B no.3
• /
• pp.201-208
• /
• 2012

Accurately segmenting lumen border in intravascular ultrasound images (IVUS) is very important to study vascular wall architecture for diagnosis of the cardiovascular diseases. After each of IVUS image is transformed to a polar coordinated image, initial points are detected using wavelet transform. Then, lumen border is initialized as the set of important points using non parametric probability density function and smoothing function by removing outlier initial points occurred by noises and artifacts. Finally, polynomial curve fitting is applied to obtain real lumen border using filtered important points. The evaluation of proposed method was performed with related method and the proposed method produced accurate lumen contour detection when compared to another method in most types of IVUS images.

• Journal of Advanced Navigation Technology
• /
• v.5 no.2
• /
• pp.123-133
• /
• 2001

The existing visualization methods using the satellite images or map images require complicated preprocessing stages and a large amount of visual data to represent the 3-D terrain. This paper presents a 3-D visualization method for geographical information, which enables automatic generation of 3-D terrain. It is generated based, on contour information obtained from a numerical map. This paper also introduces a method that resolves the three main problems needed to visualize 3-D terrain from contour lines such as correspondence, tiling, and branching. The virtual contour line is defined to extend a distorted contour line to have a similar shape to the corresponding contour line that is used, to generate 3-D surfaces. It helps that 3-D terrain is represented exactly and in detail.