• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.45 no.6
• /
• pp.95-101
• /
• 2008

In this paper, we present a new smoothing algorithm for variable depth mapping for real time stereoscopic image for 3D display. Proposed algorithm is based on the physical concept, called Laplacian equation and we also discuss the mapping of the depth from scene to displayed image. The approach to solve the problem in stereoscopic image which we adopt in this paper is similar to multi-region algorithm which was proposed by N.Holliman. The main difference thing in our algorithm compared with the N.Holliman's multi-region algorithm is that we use the Laplacian equation by considering the distance between viewer and object. We implement the real time stereoscopic image generation method for OpenGL on the circular polarized LCD screen to demonstrate its real functioning in the visual sensory system in human brain. Even though we make and use artificial objects by using OpenGL to simulate the proposed algorithm we assure that this technology may be applied to stereoscopic camera system not only for personal computer system but also for public broad cast system.

• Applied Microscopy
• /
• v.33 no.3
• /
• pp.187-193
• /
• 2003

When electron microscope images and selected area diffraction patterns of crystalline materials are being compared, it is important to know for the rotation of the diffraction pattern with respect to the image caused by the magnetic lens in the Electron Microscope. A well-known method to determine this rotation is to use a test crystal of $MoO_3$. But this method of determination of the rotation angle contains an uncertainty of $180^{\circ}$. Thus one has to devise another way to eliminate this uncertainty. In this paper we present a new and simple method of determining this rotation without any complexity. The method involves a process of obtaining LACBED patterns of crystalline materials. For the J2010 electron microscope, the rotation is determined to be $180^{\circ}$ and this angle remains unchanged for changing of the magnification and the camera length.

• Journal of Broadcast Engineering
• /
• v.25 no.2
• /
• pp.208-217
• /
• 2020

The classification of plant diseases by images captured by a camera sensor has been studied over past decades. A method that has gained much interest is to use image segmentation, from which statistical features are derived and analyzed by machine learning. Recently, deep learning has been adopted in this area. However, image segmentation is still a difficult task to achieve stable performance due to a variety of environmental variations. The end-to-end learning in neural network has a demerit that train images may be different from real images acquired in outdoor fields. To solve these problems, we propose superpixel-based disease classification method using end-to-end CNN (convolutional neural network) learning. Based on experiments performed on PlantVillage apple images, the classification accuracy is 98.29% and 92.43% for full-image and superpixel. As well, the multivariate F1-score is (0.98, 0.93). Therefore we validate that the method of using superpixel is comparable to that of full-image.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.35 no.6
• /
• pp.539-547
• /
• 2007

In this paper, development and tests of a real-time eye-tracker system are discussed. The tracker system tracks a user's gaze point through movement of eyes by means of vision-based pupil detection. The vision-based method has an advantage of detecting the exact positions of user's eyes. An infrared camera and a LED are used to acquire a user's pupil image and to extract pupil region, which was hard to extract with software only, from the obtained image, respectively. We develop a pupil-tracking algorithm with Kalman filter and grab the pupil images by using DSP(Digital Signal Processing) system for real-time image processing technique. The real-time eye-tracker system tracks the movements of user's pupils to project their gaze point onto a background image.

• KIISE Transactions on Computing Practices
• /
• v.21 no.6
• /
• pp.424-429
• /
• 2015

This research proposes a new system for calculating the total amount of coins in an image. The proposed system identified and classified the coins in the image in realtime. The image was obtained using a USB camera. Most previous coin calculation systems only used size information. If the size of an object was incorrectly detected, it caused a misclassification. Especially, in case of the former 10 won, it had high error rate because it was similar in size to the 50 won and 100 won coin. The proposed system combines hue histogram information with size information to reduce errors in the classification process. When we only used size information in the classification experiment of 2,290 coins, the recognition rate was on average about 88.2%. When we combined hue information with size information the recognition rate increased to about 99.3%.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.4
• /
• pp.753-758
• /
• 2009

Recently the high-end CMOS image sensors are developed, conforming to the SMIA CCP2 specification, which is a high-speed low-power serial interface based on LVDS technology. But this kind of technology trend makes the existing equipments are no longer useful, although their capability is still good enough to handle the recent image sensors if there was no interfacing problem. In this paper, we propose and realize a data protocol conversion system that translates the SMIA CCP2 serial signals into the existing 10-bit parallel signals. The proposed system is composed of a de-serializer and a FPCA chip, and thus can be constructed on a small PCB which enables easy integration between the existing equipments and the new high-end image sensors. Besides, the maximum transfer rate by the SMIA specification is also achieved on the implemented system. So it is expected that the implemented system can be used as a general-purpose protocol converter in a variety of sensor-related application fields.

• Korean Journal of Remote Sensing
• /
• v.33 no.2
• /
• pp.159-169
• /
• 2017

The Satellite Electro-Optic Payload System needsspecial requirements with the conditions of limited power consumption and the space environment of solar radiation. The acquired image quality should be mainly depend on the GSD (Ground Sampled Distance), SNR (Signal to Noise Ratio), and MTF (Modulation Transfer Function). On the well-manufactured sensor level, the thermal noise is removed on ASP (Analog Signal Processing) using the CDS (Corrective Double Sampling); the noise signal from the image sensor can be reduced from the offset signals based on the pre-pixels and the dark-pixels. The non-uniformity shall be corrected with gain, offset, and correction parameter of the image sensor pixel characteristic on the sensor control system. This paper describes the SNR enhancement method of the satellite EOS payload using the mentioned noise remove processes on the system design and operation, which is verified by tests and simulations.

• Journal of the Korean Society of Propulsion Engineers
• /
• v.21 no.2
• /
• pp.41-47
• /
• 2017

By using liquid and gaseous nitrogen as simulants, effects of pintle opening distance and simulant supplying condition on spray from pintle injector were investigated qualitatively. The experiment was performed by fixing the liquid supply pressure and varying the opening of the pintle and the supply pressure of gaseous nitrogen. Shadowgraph method with CCD camera was used for image visualization, and the differences of liquid-gas spray were compared by image post processing. In case of liquid nitrogen single injection, as the opening distance was increased, the injection speed was decreased. Therefore, the end of liquid sheet were converged to the center of spray. In the case of liquid nitrogen/Gaseous nitrogen spray, although shadowgraph images look similar to each other, It is shown that it can be analysed by image post processing.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.2
• /
• pp.114-123
• /
• 2014

Vehicle Black Box (Event Data Recorder EDR) only recognizes the general surrounding environments of load. In addition, general EDR is difficult to recognize the images of a sudden illumination change. It appears that the lens is being a severe distortion. Therefore, general EDR does not provide the clues of the circumstances of the accident. To solve this problem, we estimate the value of Normalized Luminance Descriptor(NLD) and Normalized Contrast Descriptor(NCD). Illumination change is corrected using Normalized Image Quality(NIQ). Second, we are corrected lens distortion using model of Field Of View(FOV) based on designed method of fisheye lens. As a result, we propose integration algorithm of two methods that correct distortions of images using each Gamma Correction and Lens Correction in parallel.

• Journal of Digital Contents Society
• /
• v.18 no.1
• /
• pp.159-165
• /
• 2017

In order to solve problems in automatic quality inspection of tablet capsules, computation-efficient image processing technique, appropriate threshold setting, edge detection and segmentation methods are required. And since existing automatic system for quality inspection of tablet capsules is of very high cost, it needs to be reduced through the realization of low-price hardware system. This study suggests a technique that uses low-cost camera module to obtain image and inspects dents on tablet capsules and sorting them by applying TLS curve fitting technique and edge-based image segmentation. In order to assess the performance, the major classifications algorithm of PCA, ICA and SVM are used to evaluate training time, test time and accuracy for capsule image area and curve fitting edge data sets.