• The Journal of the Korea Contents Association
• /
• v.4 no.1
• /
• pp.18-23
• /
• 2004

In this paper, we propose a new visual feature extraction method for content-based image retrieval(CBIR) based on wavelet transform which has both spatial-frequency characteristic and multi-resolution characteristic. We extract visual features for each frequency band in wavelet transformation and use them to CBIR. The lowest frequency band involves spacial information of original image. We extract L feature vectors using fuzzy homogeneity in the wavelet domain, which consider both the wavelet coefficients and the spacial information of each coefficient. Also, we extract 3 feature vectors wing the energy values of high frequency bands, and store those to image database. As a query, we retrieve the most similar image from image database according to the 10 largest homograms(normalized fuzzy homogeneity vectors) and 3 energy values. Simulation results show that the proposed method has good accuracy in image retrieval using 90 texture images.

• Journal of Satellite, Information and Communications
• /
• v.10 no.1
• /
• pp.56-61
• /
• 2015

In this paper, the 3D positioning of IoT sensors with the Unity engine of android platform based home-hub was proposde for IoT(Internet of Things) users. Especially, the monitoring of IoT sensor and battery status was designed with the clustering of IoT sensor's position. The 3D positioning of RSSI(received signal strength indicator) and angle for new IoT sensor according to clustering method was described with the cooperation of beacon and received arrival signal time. This unity engine based smart hub platform can monitor the working situation of IoT sensors, and apply 3D video with texture for the life-cycling of many IoT sensors simultaneously. rs was described with RSSI(received signal strength indicator) and received angle.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.10 no.1
• /
• pp.1-9
• /
• 2007

3D data are in great demand for pedestrian navigation recently. For pedestrian navigation, we needs to reconstruct 3D model in detail from people's eye. In order to present spatial features in detail for pedestrian navigation, it is indispensable to develop 3D model not only in outdoor environment but also in indoor environment such as underground shopping complex. However, it is very difficult to acquire 3D data efficiently by mobile mapping without GPS. In this research, 3D shape was acquired by Laser scanner, and texture by CCD(Charge Coupled Device) sensor. Continuous changes position and attitude of sensors were measured by IMU(Inertial Measurement Unit). Moreover, IMU was corrected by relative orientation of CCD images without GPS(Global Positioning System). In conclusion, Reliable, quick, and handy method for acquiring 3D data for indoor environment is proposed by a combination of a digital camera and a laser scanner with IMU.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2003.10a
• /
• pp.320-324
• /
• 2003

Recently, Virtual reality parts is applied in various fields of industry. In this paper we got under control motion of reality robot from interface manipulation in the virtual world. This paper created virtual robot using of 3D Graphic Tool. And we reappeared a similar image with reality robot put on texture the use of components of Direct 3D Graphic. Also a reality robot and a virtual robot is controlled by joystick. The developed robot consists of robot controller with vision system and host PC program. The robot and camera can move with 2 degree of freedom by independent remote controlling a user friendly designed joystick. An environment is recognized by the vision system and ultra sonic sensors. The visual mage and command data translated through 900MHz and 447MHz RF controller, respectively. If user send robot control command the use of simulator to control the reality robot, the transmitter/recever got under control until 500miter outdoor at the rate of 4800bps a second in Hlaf Duplex method via radio frequency module useing 447MHz frequency.

• Conservation Science in Museum
• /
• v.22
• /
• pp.85-96
• /
• 2019

The restoration of ceramics excavated in fragments is limited by the difficulty of inferring the overall shape of the original object. However, recent innovations in digital technology can help to overcome the limits of conventional restoration using handwork. This study explored the potential of digital technology by digitally restoring a shard from a white porcelain water dropper excavated at a kiln site at Sindae-ri. In order to complete the digital restoration, 3D scanning was applied to obtain scan data, and 3D modeling and texture mapping were performed. In this way, three-dimensional data with patterns and color information was acquired and the original form of the water dropper could be ascertained based on the shard. The study found that the data acquired from digital restoration can be used for various purposes, including for obtaining data on cross-sections or missing portions of a relic.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.10
• /
• pp.1886-1891
• /
• 2017

Denoising which is one of major research topics in the image processing deals with recovering the noisy images. Natural images are well known not only for their local but also nonlocal similarity. Patterns of unique edges and texture which are crucial for understanding the image are repeated over the nonlocal region. In this paper, a nonlocal similarity based denoising algorithm is proposed. First for every blocks of the noisy image, nonlocal similar blocks are gathered to construct a overcomplete data set which are inherently sparse in the transform domain due to the characteristics of the images. Then, the sparse transform coefficients are filtered to suppress the non-sparse additive noise. Finally, the image is recovered by aggregating the overcomplete estimates of each pixel. Performance experiments with several images show that the proposed algorithm outperforms the conventional methods in removing the additive Gaussian noise effectively while preserving the image details.

• Journal of Digital Contents Society
• /
• v.18 no.4
• /
• pp.777-785
• /
• 2017

In the modern real world, we can extract and recognize some texts to get a lot of information from the scene containing them, so the techniques for extracting and recognizing text areas from a scene are constantly evolving. They can be largely divided into texture-based method, connected component method, and mixture of both. Texture-based method finds and extracts text based on the fact that text and others have different values such as image color and brightness. Connected component method is determined by using the geometrical properties after making similar pixels adjacent to each pixel to the connection element. In this paper, we propose a method to adaptively change to improve the accuracy of text region extraction, detect and correct the slope of the image using edge and image segmentation. The method only extracts the exact area containing the text by correcting the slope of the image, so that the extracting rate is 15% more accurate than MSER and 10% more accurate than EEMSER.

• Journal of the Institute of Convergence Signal Processing
• /
• v.10 no.3
• /
• pp.164-169
• /
• 2009

This paper proposes a road detection method using BP(Back-Propagation) neural network based on texture information of the each candidate road region segmented for satellite images. To segment the candidate road regions, the histogram-based binarization method proposed by N.Otsu is firstly performed and the neighboring regions surrounding road regions are then removed. And after extracting the principal color using the histogram of the segmented foreground, the candidate road regions are classified into the regions within ${\pm}25$ of the principal color. Finally, the road regions are segmented using BP neural network based on texture information of the candidate regions. The texture information in this paper is calculated using co-occurrence matrix and is used as an input data of the BP neural network. The proposed method is based on the fact that the road has the constant intensity and shape. The experiment demonstrated the validity of the proposed method and showed 90% detection accuracy for the various images.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.6
• /
• pp.62-69
• /
• 2015

In this paper, a new frame rate up conversion (FRUC) algorithm using adaptive motion estimation (AME-FRUC) is proposed. The proposed algorithm performs extended bilateral motion estimation (EBME) conducts motion estimation (ME) processes on the static region, and extract region of interest with the motion vector (MV). In the region of interest block, the proposed AME-FRUC uses the texture block partitioning scheme and the unilateral motion estimation for improving ME accuracy. Finally, motion compensated frame interpolation (MCFI) are adopted to interpolate the intermediate frame in which MCFI is employed adaptively based on ME scheme. Experimental results show that the proposed algorithm improves the PSNR up to 3dB, the SSIM up to 0.07 and 68% lower SAD calculations compared to the EBME and the conventional FRUC algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.12
• /
• pp.2681-2690
• /
• 2010

This paper proposes 3D facial modeling system without using 3D scanner and camera or expensive software. This system enables efficient 3D facial modeling to cost reduction and effort saving for natural facial modeling. It detects edges of component of face using edge detection based on fuzzy logic from any 2D image of front face. It was mapped fitting position with 3D standard face model by detected edge more correctly. Also this system generates 3D face model more easily through floating and flexible control and texture mapping after fitting that connection of control point on detected edge from 2D image and mesh of 3D standard face model.