Image processing methods can be broadly classified into hardware and software processing. Hardware is suitable for embedded systems because of its high performance and low power consumption. In hardware development, high-level synthesis is often used because of its ease of development. However, in order to generate high-performance hardware, it is necessary to write at the software level, considering the configuration of the hardware. Since sorting algorithms are often used inside image processing, it is necessary to generate high-performance sorting algorithm hardware. In previous research, methods for generating high-performance sorting hardware using high-level synthesis and performance comparisons have been conducted, but no comparison has been made for image processing as a whole. In this study, we will examine the dynamic background subtraction method, which is an image processing method that uses sorting algorithms. As a result, it was found that simple algorithms such as bubble sort and odd-even sort can realize pipeline processing, which is a feature of hardware, and produce high-performance image processing hardware.
{"title":"Effect of Sorting Algorithms on High-level Synthesized Image Processing Hardware","authors":"Kohei Shinyamada, A. Yamawaki","doi":"10.12792/icisip2021.005","DOIUrl":"https://doi.org/10.12792/icisip2021.005","url":null,"abstract":"Image processing methods can be broadly classified into hardware and software processing. Hardware is suitable for embedded systems because of its high performance and low power consumption. In hardware development, high-level synthesis is often used because of its ease of development. However, in order to generate high-performance hardware, it is necessary to write at the software level, considering the configuration of the hardware. Since sorting algorithms are often used inside image processing, it is necessary to generate high-performance sorting algorithm hardware. In previous research, methods for generating high-performance sorting hardware using high-level synthesis and performance comparisons have been conducted, but no comparison has been made for image processing as a whole. In this study, we will examine the dynamic background subtraction method, which is an image processing method that uses sorting algorithms. As a result, it was found that simple algorithms such as bubble sort and odd-even sort can realize pipeline processing, which is a feature of hardware, and produce high-performance image processing hardware.","PeriodicalId":431446,"journal":{"name":"The Proceedings of The 8th International Conference on Intelligent Systems and Image Processing 2021","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125320704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jing Zhang, Y. Endo, Yuki Yamamoto, Akiyoshi Ito, Hirokazu Oosawa, Kazuaki Fukushima, T. Akashi
Defects in automotive coated surfaces have a significant impact on consumers' purchase decisions. At present, most of the global automotive companies still rely on visual inspection to detect defects. With the development of industry4.0, in order to reduce the burden on inspectors, an inspection device is needed to help inspectors work more effectively. A defect detection system using a single camera, which filters the defect candidates using the tracking trajectories of the defect candidates on multiple frames has already proposed. However, this method has many noises for metallic color coated surfaces. This paper presents a new method to sift the defect candidates based on binarization and brightness difference. The experimental results demonstrate that this method can more effectively suppress the negative effects of sifting defect candidates. In the experiment, the F-measure are 100% for the coated surface.
{"title":"Sifting Method of Defect Candidate on Coated Automobile Roofs based on Binarization and Brightness Difference","authors":"Jing Zhang, Y. Endo, Yuki Yamamoto, Akiyoshi Ito, Hirokazu Oosawa, Kazuaki Fukushima, T. Akashi","doi":"10.12792/icisip2021.033","DOIUrl":"https://doi.org/10.12792/icisip2021.033","url":null,"abstract":"Defects in automotive coated surfaces have a significant impact on consumers' purchase decisions. At present, most of the global automotive companies still rely on visual inspection to detect defects. With the development of industry4.0, in order to reduce the burden on inspectors, an inspection device is needed to help inspectors work more effectively. A defect detection system using a single camera, which filters the defect candidates using the tracking trajectories of the defect candidates on multiple frames has already proposed. However, this method has many noises for metallic color coated surfaces. This paper presents a new method to sift the defect candidates based on binarization and brightness difference. The experimental results demonstrate that this method can more effectively suppress the negative effects of sifting defect candidates. In the experiment, the F-measure are 100% for the coated surface.","PeriodicalId":431446,"journal":{"name":"The Proceedings of The 8th International Conference on Intelligent Systems and Image Processing 2021","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129158621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qixi He, H. Takizawa, A. Ohya, M. Kobayashi, Mayumi Aoyagi
The problem of personal accidents of visually impaired individuals in public areas has become a social issue. In this study, we propose a detection method of white-cane users, which are visually impaired individuals, based on surveillance cameras and YOLO. The proposed method was applied to actual videos, and several experimental results were shown.
{"title":"Preliminary Study on Detection of White-Cane Users by Surveillance Cameras and YOLO","authors":"Qixi He, H. Takizawa, A. Ohya, M. Kobayashi, Mayumi Aoyagi","doi":"10.12792/icisip2021.018","DOIUrl":"https://doi.org/10.12792/icisip2021.018","url":null,"abstract":"The problem of personal accidents of visually impaired individuals in public areas has become a social issue. In this study, we propose a detection method of white-cane users, which are visually impaired individuals, based on surveillance cameras and YOLO. The proposed method was applied to actual videos, and several experimental results were shown.","PeriodicalId":431446,"journal":{"name":"The Proceedings of The 8th International Conference on Intelligent Systems and Image Processing 2021","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125430412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the widespread use of smartphones and wearable devices, various research has been conducted using built-in sensors. For example, height estimation and road condi-tion estimation have been performed. In addition, behavioral estimation of the smartphone holder, possession position estimation, and person estimation has also been conducted. However, most of the measurement data is taken by fixing the possession position at a single location and not considering it in actuality when estimating behavior. In this research, we aim to estimate a person’s behavior by considering multiple possession positions. It is necessary to estimate a person’s behavior by considering various possession positions when using behavior estimation as a system. In addition, by treat-ing the time series data acquired by the 3-axis acceleration sensor as a 2-dimensional image using the GAF algorithm, (1) class classification by machine learning is performed.
{"title":"Behavioral Estimation for Multiple Possession Positions Using Smartphone Accelerometers","authors":"Rui Kitahara, Lifeng Zhang","doi":"10.12792/icisip2021.030","DOIUrl":"https://doi.org/10.12792/icisip2021.030","url":null,"abstract":"With the widespread use of smartphones and wearable devices, various research has been conducted using built-in sensors. For example, height estimation and road condi-tion estimation have been performed. In addition, behavioral estimation of the smartphone holder, possession position estimation, and person estimation has also been conducted. However, most of the measurement data is taken by fixing the possession position at a single location and not considering it in actuality when estimating behavior. In this research, we aim to estimate a person’s behavior by considering multiple possession positions. It is necessary to estimate a person’s behavior by considering various possession positions when using behavior estimation as a system. In addition, by treat-ing the time series data acquired by the 3-axis acceleration sensor as a 2-dimensional image using the GAF algorithm, (1) class classification by machine learning is performed.","PeriodicalId":431446,"journal":{"name":"The Proceedings of The 8th International Conference on Intelligent Systems and Image Processing 2021","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121107929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shoya Makihira, Naoto Murakami, Tsunahiko Hirano, K. Doi, K. Matsunaga, S. Nishifuji, Shota Nakashima
The number of deaths from COPD in 2019 is about 6% of all deaths worldwide. The prevalence of COPD is expected to increase worldwide. Pulmonary function testing, so called spirometry is used in the diagnosis and severity assessment of COPD. There is a simple test method using expiratory and inspiratory time. Systems to measure expiratory and inspiratory time do not proposed. In this study, we propose a novel distinction method between expiratory and inspiratory sounds using biological sound sensors. The biological sound sensor consists of two units: holding and sensor units. The former fixes the sensor unit. The latter obtains biological sounds and adopts a polyurethane elastomer to match the acoustic impedance. The respiratory sounds are extracted by applying a bandpass filter to the biological sounds. Furthermore, Harmonic/Percussive Sound Separation is applied to the respiratory sounds to reduce the residual vascular sounds. The classifier between expiratory and inspiratory sounds is built with a soft margin Support Vector Machine. The feature is the power spectrum extracted from the spectrogram of respiratory sound. The classifier was built for each subject from the two respiration patterns. The proposed method was verified by the accuracy, precision, recall, and F-score. The obtained distinction accuracy was up to 86.8%, and it was possible to distinguish between expiratory and inspiratory sounds with high accuracy.
{"title":"Distinction Method between Expiratory and Inspiratory Sounds Using Biological Sound Sensor","authors":"Shoya Makihira, Naoto Murakami, Tsunahiko Hirano, K. Doi, K. Matsunaga, S. Nishifuji, Shota Nakashima","doi":"10.12792/icisip2021.022","DOIUrl":"https://doi.org/10.12792/icisip2021.022","url":null,"abstract":"The number of deaths from COPD in 2019 is about 6% of all deaths worldwide. The prevalence of COPD is expected to increase worldwide. Pulmonary function testing, so called spirometry is used in the diagnosis and severity assessment of COPD. There is a simple test method using expiratory and inspiratory time. Systems to measure expiratory and inspiratory time do not proposed. In this study, we propose a novel distinction method between expiratory and inspiratory sounds using biological sound sensors. The biological sound sensor consists of two units: holding and sensor units. The former fixes the sensor unit. The latter obtains biological sounds and adopts a polyurethane elastomer to match the acoustic impedance. The respiratory sounds are extracted by applying a bandpass filter to the biological sounds. Furthermore, Harmonic/Percussive Sound Separation is applied to the respiratory sounds to reduce the residual vascular sounds. The classifier between expiratory and inspiratory sounds is built with a soft margin Support Vector Machine. The feature is the power spectrum extracted from the spectrogram of respiratory sound. The classifier was built for each subject from the two respiration patterns. The proposed method was verified by the accuracy, precision, recall, and F-score. The obtained distinction accuracy was up to 86.8%, and it was possible to distinguish between expiratory and inspiratory sounds with high accuracy.","PeriodicalId":431446,"journal":{"name":"The Proceedings of The 8th International Conference on Intelligent Systems and Image Processing 2021","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121576156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The decarbonizing is one of the hottest topics in the world. Although the thermal power generation was still high rate in Japan, the renewable energy gradually increased. In particular, the solar power generation, which is a typical renewable energy, is increasing in Japan. Mega solar power plants increased after the 2011 Tohoku earthquake. The heavy rainfall disasters are getting larger and more powerful year after year due to the global warming, some of mega solar power plants were damaged. Typical damages of mega solar power plants were shown in this presentation, and the failure mechanism of mega solar plants was investigated through the experimental studies. Finally, geotechnical slope stability approaches were proposed for the mega solar power plant construction.
{"title":"Damage of Mega Solar Power Plants Due to Heavy Rain - Global warming and sustainable green energy -","authors":"Y. Nabeshima","doi":"10.12792/icisip2021.002","DOIUrl":"https://doi.org/10.12792/icisip2021.002","url":null,"abstract":"The decarbonizing is one of the hottest topics in the world. Although the thermal power generation was still high rate in Japan, the renewable energy gradually increased. In particular, the solar power generation, which is a typical renewable energy, is increasing in Japan. Mega solar power plants increased after the 2011 Tohoku earthquake. The heavy rainfall disasters are getting larger and more powerful year after year due to the global warming, some of mega solar power plants were damaged. Typical damages of mega solar power plants were shown in this presentation, and the failure mechanism of mega solar plants was investigated through the experimental studies. Finally, geotechnical slope stability approaches were proposed for the mega solar power plant construction.","PeriodicalId":431446,"journal":{"name":"The Proceedings of The 8th International Conference on Intelligent Systems and Image Processing 2021","volume":"32 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116206480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nobuhiro Kishigaki, Hiromitsu Ijichi, K. Yoshino, T. Tatsuoka
Work at high positions, such as the tops of transmission towers, in strong winds with more than 10 m/s of 10 minutes average wind velocity is prohibited by the Ordinance on Industrial Safety and Health in Japan. Therefore, to judge whether or not work can be performed, we studied measuring wind velocity at high positions using a drone and inclinometer, which is a simple method that does not require extra cost or labor. This method enables safe and easy measurement of approximate wind velocity at high positions.
{"title":"Study on a Wind Velocity Measurement Method at High Positions with Drones","authors":"Nobuhiro Kishigaki, Hiromitsu Ijichi, K. Yoshino, T. Tatsuoka","doi":"10.12792/icisip2021.017","DOIUrl":"https://doi.org/10.12792/icisip2021.017","url":null,"abstract":"Work at high positions, such as the tops of transmission towers, in strong winds with more than 10 m/s of 10 minutes average wind velocity is prohibited by the Ordinance on Industrial Safety and Health in Japan. Therefore, to judge whether or not work can be performed, we studied measuring wind velocity at high positions using a drone and inclinometer, which is a simple method that does not require extra cost or labor. This method enables safe and easy measurement of approximate wind velocity at high positions.","PeriodicalId":431446,"journal":{"name":"The Proceedings of The 8th International Conference on Intelligent Systems and Image Processing 2021","volume":"179 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124462910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we propose a data augmentation method using 3DCG models for nuisance wildlife detection. Nuisance wildlife damage to crops has become a major problem for farmers, leading to a decline in their motivation. There-fore, there is an urgent need for countermeasures against wildlife damage. To that end, we are developing a nuisance wildlife repellent system using a convolutional neural network (CNN). Therefore, it is necessary to collect training images of nuisance wildlife. This is a very difficult task, but the method we propose can solve it easily. We obtain experimental results that show that a CNN can be trained using the images generated by our method, and our trained model has an accuracy level of 92%.
{"title":"Data Augmentation with 3DCG Models for Nuisance Wildlife Detection using a Convolutional Neural Network","authors":"Ryoke Naoya, H. Kitakaze, Ryo Matsumura","doi":"10.12792/icisip2021.032","DOIUrl":"https://doi.org/10.12792/icisip2021.032","url":null,"abstract":"In this paper, we propose a data augmentation method using 3DCG models for nuisance wildlife detection. Nuisance wildlife damage to crops has become a major problem for farmers, leading to a decline in their motivation. There-fore, there is an urgent need for countermeasures against wildlife damage. To that end, we are developing a nuisance wildlife repellent system using a convolutional neural network (CNN). Therefore, it is necessary to collect training images of nuisance wildlife. This is a very difficult task, but the method we propose can solve it easily. We obtain experimental results that show that a CNN can be trained using the images generated by our method, and our trained model has an accuracy level of 92%.","PeriodicalId":431446,"journal":{"name":"The Proceedings of The 8th International Conference on Intelligent Systems and Image Processing 2021","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128523914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Incidence Rice Disease and Insect pest Identifition Algorithm with Shuffle Attention","authors":"Yuliang Gao, Lifeng Zhang, Li Bin","doi":"10.12792/icisip2021.028","DOIUrl":"https://doi.org/10.12792/icisip2021.028","url":null,"abstract":"","PeriodicalId":431446,"journal":{"name":"The Proceedings of The 8th International Conference on Intelligent Systems and Image Processing 2021","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132010755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Traffic signal control is one way to alleviate traffic congestion on road networks. The main method of traffic signal control is a distributed control method in which signals cooperate locally. In this study, to realize more effective control in the distributed control system, we propose a guideline for selecting the cooperation partner of each traffic signal and verify its effectiveness. In this study, the traffic signal is controlled by applying deep reinforcement learning, which is a machine-learning algorithm.
{"title":"Proposal for Selecting a Cooperation Partner in Distributed Control of Traffic Signals using Deep Reinforcement Learning","authors":"Shinya Matsuta, Naoki Kodama, Taku Harada","doi":"10.12792/icisip2021.027","DOIUrl":"https://doi.org/10.12792/icisip2021.027","url":null,"abstract":"Traffic signal control is one way to alleviate traffic congestion on road networks. The main method of traffic signal control is a distributed control method in which signals cooperate locally. In this study, to realize more effective control in the distributed control system, we propose a guideline for selecting the cooperation partner of each traffic signal and verify its effectiveness. In this study, the traffic signal is controlled by applying deep reinforcement learning, which is a machine-learning algorithm.","PeriodicalId":431446,"journal":{"name":"The Proceedings of The 8th International Conference on Intelligent Systems and Image Processing 2021","volume":"32 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113974338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：