• Journal of the Korea institute for structural maintenance and inspection
• /
• v.26 no.5
• /
• pp.30-42
• /
• 2022

Due to the increase in construction of tunnels, the burdens of maintenance works for tunnel structures have been increasing in Korea. In addition, the increase of traffic volume and aging of materials also threatens the safety of tunnel facilities, therefore, maintenance costs are expected to increase significantly in the future. Accordingly, automated condition assessment technologies like image-based tunnel scanning system for inspection and diagnosis of tunnel facilities have been proposed. For image-based tunnel scanning system, it is key to create a planar image through stitching of multiple images captured by tunnel scanning system. In this study, performance of feature-based stitching algorithms suitable for stitching tunnel scanning images was evaluated. In order to find a suitable algorithm SIFT, ORB, and BRISK are compared. The performance of the proposed algorithm was determined by the number of feature extraction, calculation speed, accuracy of feature matching, and image stitching result. As for stitching performance, SIFT algorithm was the best in all parts of tunnel image. ORB and BRISK also showed satisfactory performance and short calculation time. SIFT can be used to generate precise planar images. ORB and BRISK also showed satisfactory stitching results, confirming the possibility of being used when real-time stitching is required.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_1
• /
• pp.535-543
• /
• 2022

A drone is used to diagnose crop growth and to provide information through images in the agriculture field. In the case of using high spatial resolution drone images, growth information for each object can be produced. However, accurate object detection is required and adjacent objects should be efficiently classified. The purpose of this study is to develop a Chinese cabbage object detection algorithm using multispectral reflectance images observed from drone and computer vision techniques. Drone images were captured between 7 and 15 days after planting a Chinese cabbage from 2018 to 2020 years. The thresholds of object detection algorithm were set based on 2019 year, and the algorithm was evaluated based on images in 2018 and 2019 years. The vegetation area was classified using the characteristics of spectral reflectance. Then, morphology techniques such as dilatation, erosion, and image segmentation by considering the size of the object were applied to improve the object detection accuracy in the vegetation area. The precision of the developed object detection algorithm was over 95.19%, and the recall and accuracy were over 95.4% and 93.68%, respectively. The F1-Score of the algorithm was over 0.967 for 2 years. The location information about the center of the Chinese cabbage object extracted using the developed algorithm will be used as data to provide decision-making information during the growing season of crops.

• Journal of Practical Engineering Education
• /
• v.14 no.3
• /
• pp.543-553
• /
• 2022

A collaborative robot(Cobot) is one of the production systems presented in the 4th industrial revolution and are systems that can maximize efficiency by combining the exquisite hand skills of workers and the ability of simple repetitive tasks of robots. Also, research on the development of an efficient interface method between the worker and the robot is continuously progressing along with the solution to the safety problem arising from the sharing of the workspace. In this study, a method for controlling the robot by recognizing the worker's hand signal was presented to enhance the convenience and concentration of the worker, and the safety of the worker was secured by introducing the concept of a safety zone. Various technologies such as robot control, PLC, image processing, machine learning, and ROS were used to implement this. In addition, the roles and interface methods of the proposed technologies were defined and presented for using educational media. Students can build and adjust the educational media system by linking the introduced various technologies. Therefore, there is an excellent advantage in recognizing the necessity of the technology required in the field and inducing in-depth learning about it. In addition, presenting a problem and then seeking a way to solve it on their own can lead to self-directed learning. Through this, students can learn key technologies of the 4th industrial revolution and improve their ability to solve various problems.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.26 no.1
• /
• pp.53-62
• /
• 2006

Near infrared reflectance spectroscopy (NIRS) has been increasingly used as a rapid, accurate method of evaluating some chemical compositions in forages. Analysis of forage quality by NIRS usually involves dry ground samples. Costs might be reduced if samples could be analyzed without drying or grinding. The objective of this study was to investigate effect of sample preparations and spectral math treatments on prediction ability of chemical composition for corn silage by NIRS. A population of 112 corn silage representing a wide range in chemical parameters were used in this investigation. Samples of com silage were scanned at 2nm intervals over the wavelength range 400-2500nm and the optical data recorded as log l/Reflectance(log l/R) and scanned in overt-dried grinding(ODG), liquid nitrogen grinding(LNG) or intact fresh(IF) condition. Samples were analysed for neutral detergent fiber(NDF), acid detergent fiber(ADF), acid detergent lignin(ADL), crude protein(CP) and crude ash content were expressed on a dry-matter(DM) basis. The spectral data were regressed against a range of chemical parameters using modified partial least squares(MPLS) multivariate analysis in conjunction with four spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation(SECV). The results of this study show that NIRS predicted the chemical parameters with very high degree of accuracy(the correlation coefficient of cross validation$(R^2cv)$ range from $0.70{\sim}0.95$) in ODG. The optimum equations were selected on the basis of minimizing the standard error of prediction(SEP). The Optimum sample preparation methods and spectral math treatment were for ADF, the ODG method using 2,10,5 math treatment(SEP = 0.99, $R^2v=0.93$), and for CP, the ODG method using 1,4,4 math treatment(SEP = 0.29. $R^2v=0.91$).

• Horticultural Science & Technology
• /
• v.30 no.2
• /
• pp.162-170
• /
• 2012

The objectives of this study were to isolate and the sequence of novel $F3'H$ gene related to an anthocyanin pathway, and to confirm the expression patterns of the gene involved in the flower color variations of chrysanthemum mutants. In this study, we isolated the full-length cDNAs and the genomic DNAs of an $F3'H$ gene from a wild type (WT) chrysanthemum (cv. Argus) and its three color mutants. The sequence analysis revealed a putative open reading frame of 1,527 bp that encodes a polypeptide of 509 amino acids. Sequence homology ranged from 97% to 99% between 'Argus' and its three color mutants. The sequence analysis from the genomic DNA revealed that the chrysanthemum $DgF3'H$ gene consisted of three exons and two introns spanning a 3,830 bp length. The sizes of the gene for three mutants ranged from a shorter size of 3,828 bp to a longer size of 3,838 bp when compared to the size of WT. The total size of the two introns was 2,157 bp for WT, but those for three color mutants ranged from 2,154 bp to 2,159 bp. A result of an RT-PCR analysis indicated that the color variations of the mutants AM1 and AM2 can be partly explained by the structural modification derived from the sequencial changes in the gene caused by gamma ray. A Southern blot analysis revealed that the $DgF3'H$ gene existing as multiple copies in the chrysanthemum genome. A systemic study will be further needed to provide a genetic mechanism responsible for the color mutation and to uncover any involvement of genetic elements for the expression of the $DgF3'H$ gene for the color variation in chrysanthemum.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.18 no.2
• /
• pp.74-87
• /
• 2016

Potato phenology, growth, and yield are projected to be highly affected by global warming in the future. The objective of this study was to examine the responses of potato growth and yield to environmental elements like temperature, solar radiation, and daylength. Planting date experiments under open field condition were conducted using three cultivars differing in maturity group (Irish Cobbler and Superior as early; Atlantic as mid-late maturing) at eight different planting dates. In addition, elevated temperature experiment was conducted in four plastic houses controlled to target temperatures of ambient temperature (AT), $AT+1.5^{\circ}C$, $AT+3^{\circ}C$, and $AT+5^{\circ}C$ using cv. Superior. Tuber initiation onset was found to be hastened curve-linearly with increasing temperature, showing optimum temperature around $22-24^{\circ}C$, while delayed by longer photoperiod and lower solar radiation in Superior and Atlantic. In the planting date experiments where the average temperature is near optimal and solar radiation, rainfall, pest, and disease are not limiting factor for tuber yield, the most important determinant was growth duration, which is limited by the beginning of rainy season in summer and frost in the late fall. Yield tended to increase along with delayed tuber initiation. Within the optimum temperature range ($17^{\circ}-22^{\circ}C$), larger diurnal range of temperature increased the tuber yield. In an elevated temperature treatment of $AT+5.0^{\circ}C$, plants failed to form tubers as affected by high temperature, low irradiance, and long daylength. Tuber number at early growth stage was reduced by higher temperature, resulting in the decrease of assimilates allocated to tuber and the reduction of average tuber weight. Stem growth was enhanced by elevated temperature at the expense of tuber growth. Consequently, tuber yield decreased with elevated temperature above ambient and drop to almost nil at $AT+5.0^{\circ}C$.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.29 no.1
• /
• pp.7-12
• /
• 2009

This experiment was conducted to compare the agronomic characteristics and productivity in introduced forage pea cultivars at the experimental field. The experiment was arranged in a randomized block design with three replications. The forage pea used in this study were two cultivars ('Livioletta', 'Austrian Pea') and one Chinese milk vetch cultivar (Chinese domestic cultivar). Flowing of 'Livioletta' cultivar was May 16th and 'Austrian Pea' cultivar was 18th May, 20 days later than the former. The 'Livioletta' cultlvar showed stronger than winter hardiness of 'Austrian Pea' cultivar. Dry matter (DM) content of 'Liviotetta' and 'Austrian Pea' cultivars were 22.5% and 20.9% chinese milk vetch showed the lowest content with 17.7%. 'Austrian pea' cultivar showed the highest DM yield with 5,617 kg/ha but the DM yield of 'Livioletta' cultivar was low with 3,652 kg/ha. The yield of CP (crude protein) and TDN (total digestible nutrient) set high at 'Austrian Pea' cultivar. And 'Livioletta' and 'Austrian Pea' cultivars showed CP content with 15.5% and 14.4% but Chinese milk vetch with 19.3%. The acid detergent fiber (ADF) and neutral detergent fiber (NDF) content of 'Austrian Pea' cultivar were 23.2% and 40.3%. Therefore 'Austrian pea' cultivar seems to be suitable varieties in paddy field as winter forage crops.