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Kamewari, Ryusei*; Fujishima, Yusuke*; Kawabata, Kuniaki; Suzuki, Kenta; Sakagami, Norimitsu*; Takemura, Fumiaki*; Takahashi, Satoru*
Proceedings of the IUTAM Symposium on Optimal Guidance and Control for Autonomous Systems 2023 (IUTAM Bookseries No.40), p.85 - 101, 2024/01
Sakakibara, Takanori*; Takahashi, Satoru*; Kawabata, Kuniaki; Oda, Shoji*
2021 IEEE/SICE International Symposium on System Integration (SII 2021), Vol.2, p.517 - 523, 2021/07
Times Cited Count：0 Percentile：0(Computer Science, Interdisciplinary Applications)In biology, it is expected to understand the mechanism of herd development by analyzing crowd behavior. Currently, medaka (Oryzias latipes) is often used when conducting such research because of its ease of breeding and experimentation. However, when conducting such studies, it is very difficult to manually obtain herd data. In this article, in order to analyze the behavior of medaka, we will introduce a method to automatically extract the swimming trajectory of medaka from time-series images and acquire the data necessary for behavior analysis. In particular, the improvement of extraction accuracy is achieved by processing the overlap state and adjoin state of medaka in the image.
)Matsuda, Asahi*; Takahashi, Satoru*; Kawabata, Kuniaki; Oda, Shoji*; Kaneko, Shunichi*
Denki Gakkai Rombunshi, D, 139(4), p.424 - 432, 2019/04
Takahashi, Satoru*; Nota, Yoshiki*; Matsuda, Asahi*; Kawabata, Kuniaki; Suzuki, Tsuyoshi*; Takemura, Fumiaki*; Ogasawara, Kei*; Kaneko, Shunichi*
Journal of Signal Processing, 21(1), p.15 - 24, 2017/01
In recent years, many researchers try to observe the state of the global environment from marine information for the understanding of the global environment change. First, we introduce the recording system of underwater environment which is made by the authors. By using this system, we want to observe the change of global environment from the coral bleaching. In this paper, especially, we propose the generation method of underwater landmark which is used to measure the position of robot of oceanographic observation based on the dynamic image processing. In here, underwater landmark means the feature point in underwater image.
Takahashi, Satoru*; Okuda, Yasutake*; Kawabata, Kuniaki; Aonuma, Hitoshi*; Sato, Yutaka*; Iwata, Kenji*
Journal of Signal Processing, 20(2), p.65 - 74, 2016/03
Koike, Kenji*; Takahashi, Satoru*; Kawabata, Kuniaki; Suzuki, Tsuyoshi*; Takemura, Fumiaki*
no journal, ,
We propose a method of estimating amount of attitude change of stationary sensor node which is important to realize observation of identical spot for a long term based on the tracked position data of underwater landmark, it is called marine tag, generated on underwater image, and then in order to see a target, in here a coral, in the fixed position on image, attitude of captured image is corrected based on the estimated amount of attitude data. Then, we estimate amount of attitude change of sensor unit of stationary sensor node by optimizing the evaluation function based on Steepest Descent Method, and correct the attitude of original image with the estimated attitude data. Through some experiments, we prove the effectiveness of our proposed method.
Matsuda, Asahi*; Okuda, Yudai*; Takahashi, Satoru*; Kawabata, Kuniaki; Ogasawara, Kei*
no journal, ,
Research of monitoring of corals plays an important role in observing the natural environment on a global scale. Identifying and detecting corals amongst other objects, including marine organisms, from an image taken undersea is a difficult task. Moreover, there are many types of corals and they cannot be easily categorized automatically. Currently, texture analysis is being pursued that solves the problem of detecting and recognizing corals from pictures taken undersea; Haralick 14 conditional equations are used to calculate the texture characteristics information based on the gray level co-occurrence matrix of 256 gradations and also to perform liner discrimination analysis on the characteristics information. In this paper, we propose one algorithm of texture analysis for discrimination of undersea objects, in order to detect the corals.
Suzuki, Tsuyoshi*; Soma, Ryo*; Sawai, Kei*; Kawabata, Kuniaki; Takemura, Fumiaki*; Takahashi, Satoru*; Yamashiro, Hideyuki*
no journal, ,
We developed a wireless sensor network system, Underwater Monitoring Sensor Network (UMSN), to support the coral reef observation activities for maintaining the coral reef environment. In this paper, we examined the communication conditions of wireless communication function which is equipped on a sensor node of UMSN for verifying the performance of the communication function on the practical experiment area.
Suzuki, Tsuyoshi*; Ozeki, Ryutaro*; Sawai, Kei*; Yamashiro, Hideyuki*; Takemura, Fumiaki*; Kawabata, Kuniaki; Takahashi, Satoru*; Sagara, Shinichi*; Ogasawara, Kei*
no journal, ,
In the current study, we developed an underwater monitoring sensor network system to support the observational activities to maintain the coral reef environment. This paper describes the measurement method to detect the growth area of the coral for a quantitative evaluation of the coral condition change using fluorescence coral image by capturing the underwater monitoring sensor network.
Kitamasu, Ryo*; Takahashi, Satoru*; Kawabata, Kuniaki; Ogasawara, Kei*
no journal, ,
Research of monitoring of corals plays an important role in observing the natural environment on a global scale. Identifying and detecting corals amongst other objects, including marine organisms, from an image taken undersea is a difficult task. Moreover, there are many types of corals and they cannot be easily categorized automatically. Currently, texture analysis is being pursued that solves the problem of detecting and recognizing corals from pictures taken undersea; Haralick 14 conditional equations are used to calculate the texture characteristics information based on the gray levelco-occurrence matrix of 256 gradations and also to perform liner discrimination analysis on the characteristics information. In this paper, we propose one algorithm of texture analysis for discrimination of undersea objects, in order to detect the corals.
