• Journal of Biosystems Engineering
• /
• v.24 no.5
• /
• pp.439-444
• /
• 1999

Automated greenhouse production systems often require crop growth monitoring involving accurate quantification of plant physiological properties. Conventional methods are usually burdensome, inaccurate, and harmful to crops. A thermal image analysis system can accomplish rapid and accurate measurements of physiological-property changes of stressed crops. In this research a thermal imaging system was used to measure the leaf-temperature changes of several crops according to water deficit. Thermal images were obtained from lettuce, cucumber, pepper, and chinese cabbage plants. Results showed that there were significant differences in the temperature of stressed plants and non-stressed plants. The temperature differences between these two group of plants were 0.7 to 3$^{\circ}C$ according to species.

• Journal of Biosystems Engineering
• /
• v.24 no.1
• /
• pp.25-30
• /
• 1999

The effectiveness of many greenhouse environment control methodologies depends on the growth information of crops. Acquisition of the growth information of crops requires a non-invasive and continuous monitoring method. Crop growth monitoring system using digital imaging technique was developed to conduct non-destructive and intact plant growth analyses. The monitoring system automatically measures crop growth information sends an appropriate control signal to the nutrient solution supplying system. To develop the monitoring system, a linear model that explains the relationship between the fresh weight and the top projected leaf area of a lettuce plant was developed from an experiment. The monitoring system was evaluated buy successive lettuce growing experiments. Results of the experiments showed that the developed system could estimate the fresh weight of lettuce from a lettuce image by using the linear model and generate an EC control signal according to the lettuce growth stage.

• The Plant Pathology Journal
• /
• v.16 no.5
• /
• pp.257-263
• /
• 2000

Infection with rice blast fungus (Magnaporthe grisea) significantly reduced foliar net photosynthesis (A) of rice cultivars: Ilpoom, Hwasung, and Choochung in greenhouse experiments. By measuring the amount of diseased leaf area with a computer image analysis system, the relation between disease severity (DS) and net photosynthetic rate was curvilinearly correlated (r=0.679). Diseased leaves with 35% blast symptom can be predicted to have a 50% reduction of photosynthesis. The disease severity was linearly correlated (r=0.478) with total chlorophyll (chlorophyll a and chlorophyll b) per unit leaf area(TC). Light use efficiency was reduced by the fungal infection according to the light response curves. However, dark respiration (Rd) did not change after the fungal infection (p=0.526). Since the percent of reduction in photosynthesis greatly exceeded the percent of leaf area covered by blast lesions, loss of photosynthetic tissue on an area basis could not by itself account for the reduced photosynthesis. Quantitative photosynthetic reduction can be partially explained by decreasing TC, but cannot be explained by decreasing Rd. By photosynthesis (A)-internal CO$_2$ concentration (C$_i$ curve analysis, it was suggested that the fungal infection reduced ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) activity, ribulose-1,5-bisphosphate (RuBP) regeneration, and inorganic phosphate regeneration. Thus, the reduction of photosynthesis by blast infection was associated with decreased TC and biochemical capacity, which comprises all carbon metabolism after CO$_2$ enters through the stomata.

• Journal of Broadcast Engineering
• /
• v.15 no.1
• /
• pp.133-143
• /
• 2010

This paper proposes a quadtree image compression method which encodes images efficiently and also makes unartificial compressed images. The proposed compression method uses edge-based quadtree decomposition to preserve the significant edge-lines, and it utilizes the predictive coding scheme to exploit the high correlation of the leaf node blocks. The simulation results with $256\times256$ grayscale images verify that the proposed method yields better coding efficiency than the JPEG by about 25 percents. The proposed method can provide more natural compressed images as it is free from the ringing effect in the compressed images which used to be in the images compressed by the fixed block based encoders such as the JPEG.

• Journal of Information Processing Systems
• /
• v.15 no.4
• /
• pp.737-747
• /
• 2019

Shape description is an important and fundamental issue in content-based image retrieval (CBIR), and a number of shape description methods have been reported in the literature. For shape description, both global information and local contour variations play important roles. In this paper a new included-angular ternary pattern (IATP) based shape descriptor is proposed for shape image retrieval. For each point on the shape contour, IATP is derived from its neighbor points, and IATP has good properties for shape description. IATP is intrinsically invariant to rotation, translation and scaling. To enhance the description capability, multiscale IATP histogram is presented to describe both local and global information of shape. Then multiscale IATP histogram is combined with included-angular histogram for efficient shape retrieval. In the matching stage, cosine distance is used to measure shape features' similarity. Image retrieval experiments are conducted on the standard MPEG-7 shape database and Swedish leaf database. And the shape image retrieval performance of the proposed method is compared with other shape descriptors using the standard evaluation method. The experimental results of shape retrieval indicate that the proposed method reaches higher precision at the same recall value compared with other description method.

• Applied Microscopy
• /
• v.42 no.3
• /
• pp.147-150
• /
• 2012

A recently introduced helium ion microscopy (HIM) was employed to observe uncoated pine leaf specimens. Adult leaves were collected from the seedlings of Pinus densiflora and P. rigida, air-dried at room temperature, and observed by HIM without metal coating. Ovoid or round stomata and distinct Florin rings could be discerned. The epicuticular waxes were present in the epistomatal chambers and Florin rings of stomata on the leaf surface. The epicuticular waxes were mostly straight, cylindrical, and ca. 1 ${\mu}m$ in length. The epistomatal chambers of P. rigida were filled with the epicuticular waxes, whereas those of P. densiflora were not filled with the epicuticular waxes. Based on their micromorphology, the epicuticular wax structures of the pine species were identified as tubules. These results suggest that the HIM could be used for the investigation of the plant stomata and epicuticular waxes of uncoated plant leaves. Due to the smaller ion probe and interaction volume, the HIM has advantages over conventional field emission scanning electron microscopy in terms of image resolution and charge neutralization.

• Journal of the Korean Wood Science and Technology
• /
• v.35 no.2
• /
• pp.9-15
• /
• 2007

A comparative study of the structure and organization of the primary and secondary walls in different types of tropical plant waste fibers was carried out using transmission electron microscopy (TEM). The thickness of each layer was also measured using Image Analyzer. TEM micrographs haveconfirmed that cell wall structure of all six types of tropical plant waste fibers (empty fruit bunch, oil palm frond, oil palm trunk, coir, banana stem and pineapple leaf) has the same ultrastructure with wood fibre. The fibers consisted of middle lamella, primary and thick secondary wall with different thickness for different types of fibers. The secondary wall was differentiated into a $S_1$ layer, a unique multi-lamellae $S_2$ layer, and $S_3$ layer.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.14 no.4
• /
• pp.22-31
• /
• 2005

The purpose of this study is to design a flexural structure that has a function of pan and tilt for an artificial eyeball. The artificial eyeball system has a function of image stabilization, which compensate panning and tilting vibration of the body on which the artificial eyeball is attached. The target closed loop control bandwidth is 50Hz, so the mechanical resonance frequency is required to be more than the control bandwidth, which is a tough design problem because of a big mass of camera and actuator. In this study, the design process including the selection of the principal parameters by numerical analysis with ANSYS will be described, as well as the design results and frequency response.

• Proceedings of the Korea Contents Association Conference
• /
• 2018.05a
• /
• pp.459-460
• /
• 2018

In this paper, we present a data augmentation method that generates synthetic plant disease images using Generative Adversarial Networks (GANs). We propose a training scheme that first uses classical data augmentation techniques to enlarge the training set and then further enlarges the data size and its diversity by applying GAN techniques for synthetic data augmentation. Our method is demonstrated on a limited dataset of 2789 images of tomato plant diseases (Gray mold, Canker, Leaf mold, Plague, Leaf miner, Whitefly etc.).

• Journal of Bio-Environment Control
• /
• v.32 no.4
• /
• pp.366-376
• /
• 2023

This study was conducted to develop a model for predicting the growth of kimchi cabbage using image data and environmental data. Kimchi cabbages of the 'Cheongmyeong Gaual' variety were planted three times on July 11th, July 19th, and July 27th at a test field located at Pyeongchang-gun, Gangwon-do (37°37' N 128°32' E, 510 elevation), and data on growth, images, and environmental conditions were collected until September 12th. To select key factors for the kimchi cabbage growth prediction model, a correlation analysis was conducted using the collected growth data and meteorological data. The correlation coefficient between fresh weight and growth degree days (GDD) and between fresh weight and integrated solar radiation showed a high correlation coefficient of 0.88. Additionally, fresh weight had significant correlations with height and leaf area of kimchi cabbages, with correlation coefficients of 0.78 and 0.79, respectively. Canopy coverage was selected from the image data and GDD was selected from the environmental data based on references from previous researches. A prediction model for kimchi cabbage of biomass, leaf count, and leaf area was developed by combining GDD, canopy coverage and growth data. Single-factor models, including quadratic, sigmoid, and logistic models, were created and the sigmoid prediction model showed the best explanatory power according to the evaluation results. Developing a multi-factor growth prediction model by combining GDD and canopy coverage resulted in improved determination coefficients of 0.9, 0.95, and 0.89 for biomass, leaf count, and leaf area, respectively, compared to single-factor prediction models. To validate the developed model, validation was conducted and the determination coefficient between measured and predicted fresh weight was 0.91, with an RMSE of 134.2 g, indicating high prediction accuracy. In the past, kimchi cabbage growth prediction was often based on meteorological or image data, which resulted in low predictive accuracy due to the inability to reflect on-site conditions or the heading up of kimchi cabbage. Combining these two prediction methods is expected to enhance the accuracy of crop yield predictions by compensating for the weaknesses of each observation method.