• Tunnel and Underground Space
• /
• v.13 no.5
• /
• pp.373-388
• /
• 2003

The investigation on the rock discontinuity geometry has been usually undergone by direct measurement on the rock exposures. But this sort of field work has disadvantages, which we, for example, restriction of surveying areas and consuming excessive times and labors. To cover these kinds of disadvantages, image processing could be regarded as an altemative way, with additional advantages such as automatic and objective tools when used under adequate computerized algorithm. This study was focused on the recognition of the rock discontinuities captured in the image of rock exposure by digital camera and the production of the discontinuity map automatically. The whole process was written using macro commands builtin image analyzer, ImagePro Plus. ver 4.1(Media Cybernetic). The procedure of image processing developed in this research could be divided with three steps, which are enhancement, recognition and extraction of discontinuity traces from the digital image. Enhancement contains combining and applying several filters to remove and relieve various types of noises from the image of rock surface. For the next step, recognition of discontinuity traces was executed. It used local topographic features characterized by the differences of gray scales between discontinuity and rock. Such segments of discontinuity traces extracted from the image were reformulated using an algorithm of computer decision-making criteria and linked to form complete discontinuity traces. To verify the image processing algorithms and their sequences developed in this research, discontinuity traces digitally photographed on the rock slope were analyzed. The result showed about 75～80% of discontinuities could be detected. It is thought to be necessary that the algorithms and computer codes developed in this research need to be advanced further especially in combining digital filters to produce images to be more acceptable for extraction of discontinuity traces and setting seed pixels automatically when linking trace segments to make a complete discontinuity trace.

• Journal of IKEEE
• /
• v.24 no.3
• /
• pp.838-844
• /
• 2020

In this paper, we propose an efficient Viterbi processor using Joint Viterbi detection and decoding (JVDD) algorithm for a for bluetooth low energy (BLE) system. Since the convolutional coded Gaussian minimum-shift keying (GMSK) signal is specified in the BLE 5.0 standard, two Viterbi processors are needed for detection and decoding. However, the proposed JVDD scheme uses only one Viterbi processor by modifying the branch metric with inter-symbol interference information from GMSK modulation; therefore, the hardware complexity can be significantly reduced without performance degradation. Low-latency and low-complexity hardware architecture for the proposed JVDD algorithm was proposed, which makes Viterbi decoding completed within one clock cycle. Viterbi Processor RTL synthesis results on a GF55nm process show that the gate count is 12K and the memory unit and the initial latency is reduced by 33% compared to the modified state exchange (MSE).

• Analytical Science and Technology
• /
• v.36 no.5
• /
• pp.205-215
• /
• 2023

In the present study, an analytical method was proposed for detecting trifluralin in aquatic products at trace concentrations. The method employed QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) and gas chromatography coupled with tandem mass spectrometry (GC-MS/MS) as the sample preparation and measurement, respectively. The effect of the aqueous phase volume used in the QuEChERS was demonstrated, and the ratio of 10:10 (mL) between water and acetonitrile phase was used for 5 g of sample. Besides, dSPE using C18 and primary-secondary amine (PSA) was applied to remove the potential interferences from the food matrices, indicating no remarkable analyte loss. The linear range was built up from 0.50 ㎍ L^-1 to 3.0 ㎍ L^-1 (R² = 0.9993). Other criteria, i.e., repeatability (RSD_r = 0.86-1.96 %), reproducibility (RSD_R = 1.09-2.01 %), and recovery (over 90 %), were in accordance with Appendix F of AOAC (2016) for method performance. Although no trifluralin was detected for the commercial samples (fish, shrimp, and breaded shrimp), the spiked samples performed favorable recoveries and precision.

• Journal of Biosystems Engineering
• /
• v.37 no.1
• /
• pp.65-74
• /
• 2012

Purpose: An autonomous robot was developed for harvesting strawberries cultivated in bench-type systems. Methods: The harvest robot consisted of four main components: an autonomous vehicle, a manipulator with four degrees of freedom (DOF), an end effector with two DOFs, and a color computer vision system. Strawberry detection was performed based on 3D image and distance information obtained from a stereo CCD color camera and a laser device, respectively. Results: In this work, a Cartesian type manipulator system was designed, including an intermediate revolute axis and a double driven arm-based joint axis, so that it could generate collision-free motions during harvesting. A DC servomotor-driven end-effector, consisting of a gripper and a cutter, was designed for gripping and cutting the strawberry stem without damaging the strawberry itself. Real-time position tracking algorithms were developed to detect, recognize, trace, and approach strawberries under natural light conditions. Conclusion: The developed robot system could harvest a strawberry within 7 seconds without damage.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.4
• /
• pp.851-859
• /
• 2011

In this paper, we propose the method that automatically extracts the silhouette and the joints of consecutive input image, and track joints to trace object for interaction between human and computer. Also the proposed method presents the action of human being to map human body using joints. To implement the algorithm, we model human body using 14 joints to refer to body size. The proposed method converts RGB color image acquired through a single camera to hue, saturation, value images and extracts body's silhouette using the difference between the background and input. Then we automatically extracts joints using the corner points of the extracted silhouette and the data of body's model. The motion of object is tracted by applying block-matching method to areas around joints among all image and the human's motion is mapped using positions of joints. The proposed method is applied to the test videos and the result shows that the proposed method automatically extracts joints and effectively maps human body by the detected joints. Also the human's action is aptly expressed to reflect locations of the joints