• Proceedings of the IEEK Conference
• /
• 2002.07b
• /
• pp.1256-1259
• /
• 2002

In this paper, we have proposed license plate recognition system for multi-national vehicle license plate using geometric features along with hybrid and seven segment pattern vectors. In the proposed system, we suggested to find horizontal and vertical relation after going through preparation process with inputted real-time license plate image of Korea and Japan, and then to classify license plate with using characteristic and geometric information of license plates. It classifies the extracted license plate images into letters and numbers, such as local name, local number, classification character and license consecutive numbers, and recognize license plate of Korea and Japan by applying hybrid and seven segments pattern vectors to classified letter and number region. License plate extraction step of the proposed system uses width and length information along with relative rate of Korean and Japanese license plate. Moreover, it exactly segmentation by letters with using each letter and number position information within license plate region, and recognizes Korean and Japanese license plates by applying hybrid and seven segment pattern vectors, containing characteristics related to letter size and movement within segmented letter area. As the result of testing the proposed system in real experiment, it recognized regardless of external lighting conditions as well as classifying license plates by nations, Korea and Japan. We have developed a system, recognizing regardless of inputted structural character of vehicle licenses and external environment.

• Journal of the Institute of Electronics Engineers of Korea TE
• /
• v.39 no.4
• /
• pp.379-388
• /
• 2002

In this paper, the real-time algorithm is proposed for automatic detection of the face and facial features. In the face region, we extracted eyes, nose, mouth and so forth. There are two methods to extract them; one is the method of using the location information of them, other is the method of using Gaussian second derivatives filters. This system have high speed and accuracy because the facial feature extraction is processed only by detected face region, not by whole image. There are some kinds of good experimental result for the proposed algorithm; high face detection rate of 95%, high speed of lower than 1sec. the reduction of illumination effect, and the compensation of face tilt.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.47 no.9
• /
• pp.24-29
• /
• 2010

This paper presents the RF modeling for silicon nanowire MOSFET with 30 nm channel length and 5 nm channel radius. Equations for analytical parameter extraction are derived by analysis of Y-parameter. Accuracies of the new model and extracted parameters have been verified by 3-dimensional device simulation data up to 100 GHz. The model verifications are performed under conditions of saturation region ($V_{gs}$ = $_{ds}$ = 1 V) and linear region ($V_{gs}$ = 1 V, $V_{ds}$ = 0.5 V). The RMS modeling error of Y-parameters was calculated to be 1 %.

• Proceedings of the KSRS Conference
• /
• 2008.10a
• /
• pp.173-176
• /
• 2008

Lake studies play an important role in water management, ecology, and other environmental issues. Typically, monitoring lake levels is the first step on the lake studies. However, for the Prairie Pothole Region (PPR) of North America having millions of small lakes and potholes, on-site measurement for lake levels is almost impossible with the conventional gage stations. Therefore, we employed Geographic Information System (GIS) and remote sensing approach with the Shuttle Radar Topography Mission data to extract lake levels. Several image processing techniques were used to extract lake levels for January, 2000 as a one-time snapshot which will be useful in historic lake level reconstruction. This study is associated with other remote sensing datasets such as Landsat imagery and Digital Orthophoto Quadrangle (DOQ). In this research, firstly, image processing techniques like FFT filtering, Lee-sigma, masking with Canny Edge Detector, and contouring were tested for lake level estimation. The semi-automated contouring technique was developed to accomplish the bulk processing for large amount of lakes in this region. Also, effectiveness of each method for bulk processing was evaluated.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.11 no.2
• /
• pp.41-47
• /
• 2007

A fine segmentation algorithm is proposed for extracting objects in an image, which have both weak boundaries and highly non-convex shapes. The image has simple background colors or simple object colors. Two concepts, geometric attraction-driven flow (GADF) and edge-regions are combined to detect boundaries of objects in a sub-pixel resolution. The main strategy to segment the boundaries is to construct initial curves close to objects by using edge-regions and then to make a curve evolution in GADF. Since the initial curves are close to objects regardless of shapes, highly non-convex shapes are easily detected and dependence on initial curves in boundary-based segmentation algorithms is naturally removed. Weak boundaries are also detected because the orientation of GADF is obtained regardless of the strength of boundaries. For a fine segmentation, we additionally propose a local region competition algorithm to detect perceptible boundaries which are used for the extraction of objects without visual loss of detailed shapes. We have successfully accomplished the fine segmentation of objects from images taken in the studio and aphids from images of soybean leaves.

• Journal of Sensor Science and Technology
• /
• v.8 no.2
• /
• pp.154-162
• /
• 1999

In this paper, we acquired EBT section images of lung parenchyma using fabricated spirometric gating device and proposed new energy function based on dynamic contour model in order to extracted the contour of the lung parenchyma in EBT images. In EBT images, gray level of the lungs is lower than other region. we extracted the lungs contour using the new energy function considering gray level and contour vector of the lung parenchyma region from EBT images. As we compared the proposed method with the conventional method, we confirmed that detection method using proposed energy function was valid.

• Journal of Korean Society for Geospatial Information Science
• /
• v.23 no.3
• /
• pp.85-93
• /
• 2015

This paper mainly introduces the methods of extracting landslide information using ALOS(Advanced Land Observing Satellite) images and GIS(Geographical Information System) technology. In this study, we classified images using three different methods which are the unsupervised the supervised and the PCA(Principal Components Analysis) for extracting landslide information based on characteristics of ALOS image. From the image classification results, we found out that the quality of classified image extracted with PCA supervised method was superior than the other images extracted with the other methods. But the accuracy of landslide information extracted from this image classification was still very low as the pixels were very similar between the landslide and safety regions. It means that it is really difficult to distinguish those areas with an image classification method alone because the values of pixels between the landslide and other areas were similar, particularly in a region where the landslide and other areas coexist. To solve this problem, we used the LSM(Landslide Susceptibility Map) created with ArcView software through weighted overlay GIS method in the areas. Finally, the developed LSM was applied to the image classification process using the ALOS images. The accuracy of the extracted landslide information was improved after adopting the PCA and LSM methods. Finally, we found that the landslide region in the study area can be calculated and the accuracy can also be improved with the LSM and PCA image classification methods using GIS tools.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2008.06a
• /
• pp.97-98
• /
• 2008

n-ZnO/p-Si heterostructure is a good candidate for ZnO-based heterojunction light emitting diodes(LED) because of its competitive price and lower driving voltage. However, the conventional LED shows much lower extraction efficiency, because it has small top contact and large backside contact. In this structure, the injected current from the top contact enters the active region underneath the top contact. Thus, the emitted light is hindered by the opaque top contact. This problem can be solved by using a current-blocking layer(CBL) that prevents the current injection into the active region below the top contact.

• The KIPS Transactions:PartB
• /
• v.10B no.5
• /
• pp.521-526
• /
• 2003

In this paper, we propose a geometric active contour model based on intensity information and curve evolution for detecting region boundaries. We put boundary extraction problem as the minimization of the difference between the average intensity of the region and the intensity of the expanding closed curves. We used level set theory to implement the curve evolution for optimal solution. It offered much more freedom in the initial curve position than a general active contour model. Our methods could detect regions whose boundaries are not necessarily defiened by gradient compared to general edge based methods and detect multiple boundaries at the same time. We could improve the result by using anisotropic diffusion filter in image preprocessing. The performance of our model was demonstrated on several data sets like CT and MRI medical images.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 1999.06a
• /
• pp.159-164
• /
• 1999

Homogeneous but distinct visual objects having low-contrast boundaries are usually merged in most of the segmentation algorithms. To alleviate this problem, an efficient image segmentation algorithm based on a bottom-up approach is proposed by using spatial domain information only. For initial image segmentation, we adopt an efficient marker extraction algorithm conforming to the human visual system. Then, two region-merging algorithms are successively applied so that homogeneous visual objects can be represented as simple as possible without destroying low-contrast real boundaries among them. The resultant segmentation describes homogeneous visual objects with few regions while preserving semantic object shapes well. Finally, a size-based region decision procedure may be applied to represent complex visual objects simpler, if their precise semantic contents are not necessary. Experimental results show that the proposed image segmentation algorithm represents homogeneous visual objects with a few regions and describes complex visual objects with a marginal number of regions with well-preserved semantic object shapes.