Chawan Koopipat

UAV-based multispectral image analysis system with semantic computing for agricultural health conditions monitoring and real-time management

Nowadays, UAV is widely used in several research and industrial fields. One of the highly beneficial features is that it is able to be utilized to capture aerial images in high-resolution for environmental study or detecting disaster phenomena quickly. This paper presents a multispectral image analysis system for aerial images that captured by multispectral camera, which are mounted on an unmanned autonomous vehicle (UAV) or Drone, and discusses an application of semantic computing system for agricultural health condition monitoring and analysis. In our experiments, we analyze multispectral images to detect healthy and unhealthy conditions of agricultural area and interpret the keyword of plant health conditions for user. We also propose the SPA process for real-time farming area management. As a case study, we conducted an experiment on rye fields in Latvia.

Noncontact pulse wave detection by two-band infrared video-based measurement on face without visible lighting

In this paper, we propose a novel noncontact pulse wave monitoring method that is robust to fluctuations in illumination through use of two-band infrared video signals. Because the proposed method uses infrared light for illumination, the method can be used to detect a pulse wave on a human face without visible lighting. The corresponding two-band pixel values in the video signals can be separated into hemoglobin and shading components by application of a separation matrix in logarithmic space for the two pixel values. Because the shading component has been separated, the extracted hemoglobin component is then robust to fluctuations in the illumination. The pixel values in the region of interest were spatially averaged over all the pixels of each frame. These averaged values were then used to form the raw trace signal. Finally, the pulse wave and the corresponding pulse rate were obtained from the raw trace signal through several signal processing stages, including detrending, use of an adaptive bandpass filter, and peak detection. We evaluated the absolute error rate for the pulse rate between the estimated value and the ground truth obtained using an electrocardiogram. In the experiments, we found that the performance of the proposed method was greatly improved compared with that of conventional methods using single-band infrared video.

UAV-based multispectral aerial image retrieval using spectral feature and semantic computing

This research proposes the multispectral image retrieval method by using spectral feature and semantic computing which is not many studies have focused. The main contributions are to enhance the effectiveness and advantageous of global environmental analysis system and realize semantic associative search and analysis. In this work, we study multispectral image retrieval using spectral feature computed in multispectral semantic-image space. The multispectral semantic-image space is supposing to realize the interpretation of substance (materials) on earth surface which can be provided the analyzed results as human-level interpretation. Our essential approach is utilizing the semantic computing to measure the similarity between multispectral image and the meaningful keywords which according to the users contexts. Our research results found that this method possible to acquire the spectral feature from the multispectral image and could be used in multispectral image retrieval. In this study, a multispectral image is used as the image query according to users query contexts. Moreover, the method performance of UAV-based multispectral aerial image retrieval using spectral feature and semantic computing is measured based on the queries with three contexts of multispectral image which is indicated by previous study on agricultural monitoring system and semantic interpretation model.

Color Tolerance of Identity Color of Chulalongkorn University on General Print

Chulalongkorn University has a long historical background. Pink color is known as the identity color. To be more specific on which pink colors of general prints are acceptable for the identity color of Chulalongkorn University, printed samples with the identity color were collected and measured to find the differences among the printed colors. Then the Natural Color System (NCS) colors were determined corresponding to the printed samples. The obtained NCS colors were used as samples in the experiment. A standard color was obtained from the color of pink cushion placed under Prakeaw, an emblem of Chulalongkorn University. Measurements were taken at the same specific light source as in printed samples. Comparison was then made to determine the color tolerance. A method of pass/fail tolerance was adopted to evaluate the optimum color difference between the identity color and the color of general prints by comparing the results of color measuring device against that of visual assessment. A group of 101 observers were involved to find their perception acceptability of printed pink samples against identity color or standard pink color. The color different equations, E94 and CIEE2000 were employed.