ENOMOTO Koichiro

写真a

Title

Lecturer

Campus Career 【 display / non-display

  • University of Shiga Prefecture  School of Engineering  Department of Electronic Systems Engineering  Lecturer   2019.04 - Now

  • University of Shiga Prefecture  School of Engineering  Department of Electronic Systems Engineering  Assistant Professor   2018.04 - 2019.03

 

Papers 【 display / non-display

  • Image processing for evaluation of papilla clearness of dried sea cucumber products

    Narita M., Sugawara A., Kuwahara Y., Enomoto K., Toda M.

    Food Science and Technology Research  Food Science and Technology Research  27 (1)   69 - 74  2021.01

    10.3136/fstr.27.69  Joint Work  

    [Abstract]

    We aimed to establish an objective method to evaluate the quality of dried sea cucumber products. Clearness of papillae on the body wall affects the quality and commercial value of this luxury seafood. Unfortunately, an objective method for evaluating papilla clearness remains to be developed. We digitalized clearness of papillae from dried sea cucumber products images using TouchDeMeasure. This software application was developed by the authors. Using this tool, we measured body length (BL), total perimeter including all papillae (TP), and ellipse perimeter excluding the papillae (EP). Results showed that TP/BL, TP/EP, and (TP-EP)/BL values for a clear papilla were significantly higher than those for an unclear papilla. Additionally, we confirmed that these parameters corresponded with the grading levels used by a connoisseur. These experimental results show that our method digitally analyzes the clearness of papillae to evaluate the quality of dried sea cucumber products.

  • Removal of floating particles from underwater images using image transformation networks

    Li L., Komuro T., Enomoto K., Toda M.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  12662 LNCS    2021.01

    10.1007/978-3-030-68790-8_32  Joint Work  

    [Abstract]

    In this paper, we propose three methods for removing floating particles from underwater images. The first two methods are based on Generative Adversarial Networks (GANs). The first method uses CycleGAN which can be trained with an unpaired dataset, and the second method uses pix2pixHD that is trained with a paired dataset created by adding artificial particles to underwater images. The third method consists of two-step process – particle detection and image inpainting. For particle detection, an image segmentation neural network U-Net is trained by using underwater images added with artificial particles. Using the output of U-Net, the particle regions are repaired by an image inpainting network Partial Convolutions. The experimental results showed that the methods using GANs were able to remove floating particles, but the resolution became lower than that of the original images. On the other hand, the results of the method using U-Net and Partial Convolutions showed that it is capable of accurate detection and removal of floating particles without loss of resolution.

  • Investigation of influence of change of noise variance in removing floating matter from underwater image using kalman filter

    Egashira M., Migita M., Enomoto K., Komuro T., Toda M., Kuwahara Y., Tezuka N.

    Lecture Notes in Electrical Engineering  Lecture Notes in Electrical Engineering  589   987 - 993  2020.01

    10.1007/978-981-32-9441-7_102  Joint Work  

    [Abstract]

    © Science Press 2020. In this paper, we propose a method for eliminating image noise (from sand, algae, bubbles, etc.) that is transferred when capturing underwater images. In detail, we separate the input of a moving underwater image into a slowly changing background and foreground moving at a certain speed using Kalman filter and object tracking. In this research, we examined the difference in image quality of the output image by changing the noise variance given to the Kalman filter.

  • A Study of Bottom Sediment Classification System Using Seabed Images

    J. Kitagawa, K. Enomoto, M. Toda, K. Miyoshi, Y. Kuwahara,

     Sensors and Materials    2019.03

    Joint Work  Joint(The vice charge)

  • Productivity and thallus toughness trade-off relationship in marine macroalgae from the Japan Sea

    Sakanishi Y., Kasai H., Enomoto K., Toda M., Tanaka J.

    Phycological Research  Phycological Research    2019.01

    10.1111/pre.12375  Joint Work  

    [Abstract]

    © 2019 Japanese Society of Phycology Trade-offs are considered key to understanding mechanisms supporting the coexistence of multiple plant species. Thus, understanding the mechanisms underlying trade-offs is expected to contribute to conservation and management of macroalgal beds composed of diverse macroalgae of rocky shore ecosystems. To test the occurrence of trade-offs between productivity and thallus toughness as well as pair-wise thallus trait relationships that are expected to indirectly relate to any trade-offs, traits and relationships for 13 species of macroalgae from the central area along the Japan Sea coast of Honshu, Japan were examined. In each species we examined for photosynthetic capacity per unit biomass (as A mass ) and nitrogen (i.e., photosynthetic nitrogen-use efficiency, PNUE), nitrogen content (as N mass ), thallus mass per unit thallus area (as TMA) and force required to penetrate the thallus (as F p , a common index of leaf toughness in land plants by punch test). A significant negative correlation indicating a trade-off between productivity and thallus toughness was found between A mass or PNUE and F p . Pair-wise relationships that were expected to indirectly relate to the trade-off were as follows. A mass was positively correlated with N mass . Thalli with high N mass extensively utilizing nitrogen in the photosynthetic parts, and consequently exhibiting elevated metabolic rates. Moreover, thalli with high N mass tended to be associated with low TMA, and N mass decreased with increasing TMA. A significant negative correlation was observed between TMA and A mass or PNUE because of the linkage of high A mass or PNUE with high N mass and high N mass associated with low TMA, while a significant positive correlation was observed between TMA and F p . The two correlations indicate a physiological and structural trade-off, which underlies the interdependency of thallus traits. Results of multivariate analyses also indicated that the thallus traits interdependently vary across a single axis based on the trade-off.

  • Fluorescent Staining for Detecting Larvae of the Japanese Scallops Mizuhopecten Yessoensis

    K. Enomoto, M. Toda, Y. Shimizu, Y. Kuwahara

     Transactions of the Institute of Systems, Control and Information Engineers    2018.12

    Joint Work  Joint(The main charge)

  • Effect of seawater turbulence on formation of coral primary polyp skeletons

     Shinya Iwasaki, Atsushi Suzuki, Akira Iguchi, Osamu Sasaki, Harumasa Kano, Yoshikazu Ohno, Koichiro Enomoto

     Coral Reefs    2018.03

    Joint Work  Joint(The vice charge)

  • Circatidal activity rhythms in the soldier crab Mictyris guinotae

    T. Moriyama, K. Enomoto, H. Kawai, S. Watanabe

     Biological Rhythm Research  48 (1)   129 - 139  2017.01

    Joint Work  Joint(The vice charge)

  • Visual image of neighbors to elicit wandering behavior in the soldier crab

    T. Moriyama, J. Mashiko, T. Matsui, K. Enomoto, T. Matsui, K. Iizuka, M. Toda, and Y. P. Gunji

     Artificial Life and Robotics  21 (3)   247 - 252  2016.09

    Joint Work  

  • Extraction Method of Scallop Area from Sand Seabed Images

    K. Enomoto, M. Toda, and Y. Kuwahara

     IEICE TRANSACTIONS on Information and Systems  97 (1)   130 - 139  2014.01

    Joint Work  Joint(The main charge)

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Conferences 【 display / non-display

  • Proposal of bottom sediment classification system using seabed image

    Workshop on Sensors in Agriculture and Fishery Industries  2018.02

  • Study on the Auto Extraction System for the Giant Jellyfish Nemopilema Nomurai from Underwater Video

    Japan-Korea Joint Workshop on Frontiers of Computer Vision (FCV2016)  2016.02

  • Power-saving Evaluation of the Demand Responsive Intelligent Bus Stop System by Image Processing

    Japan-Korea Joint Workshop on Frontiers of Computer Vision (FCV2016)  2016.02

  • Visual image of neighbors to elicit wandering behavior in the soldier crab Mictyris guinotae

    International Symp. on SWARM Behavior and Bio-inspired Robotics  2015.10

  • Discussion on a Method to Extract Scallop Using Line Convergence Index Filter from Granule-sand Seabed Videos

    IAPR Conf. on Machine Vision Applications (MVA2015)  2015.05

  • Interactive Facial Expression Reader and Extension to First Impression Improver

    Proceedings of the 2nd International Conference on Perception and Machine Intelligence  2015.02

  • Spatially Adaptive Image Defogging using color characteristics

    Japan-Korea Joint Workshop on Frontiers of Computer Vision (FCV2015)  2015.01

  • Detection Method of Scallop and Asteroid from Seabed Video

    IAPR Conf. on Machine Vision Applications  2013.05

  • Detection Method of Asteroid in Sand field from Seabed Video

    International Conf. on Quality Control by Artificial Vision  2013.05

  • Bottom Sediment Classification Method from Seabed Image for Automatic Counting System of Scallop

    International Symposium on Optomechatronic Technologies  2012.10

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