Pub Date : 2017-12-01DOI: 10.1109/PIC.2017.8359591
Hongliang He, Le Hui, Wen-Yi Gu, Shanshan Zhang, Jian Yang
Traffic sign detection system is one of the most important part of self-driving cars. It is hard to correctly detect and classify the traffic signs because of the small scale property and the complexity of road environments. In this work, we propose a novel framework of feature transferring for traffic sign detection. We improve the traffic sign detection performance in the wild by transferring digit classifier's features to a detector. Specifically, we train a convolutional neural network(CNN) classifier on a digit training set, in which each image is cropped from the traffic sign detection dataset, and then use the classifier's high-level features as an additional supervision to the detector. With the help of the additional supervision, the detector can learn a better representation of traffic sign. Extensive experiments validate the effectiveness of our approach. Our method achieves state-of-the-art performance in traffic sign detection task on the largest traffic sign detection dataset, Tsinghua-Tencent 100K.
{"title":"Transferring digit classifier's features to a traffic sign detector","authors":"Hongliang He, Le Hui, Wen-Yi Gu, Shanshan Zhang, Jian Yang","doi":"10.1109/PIC.2017.8359591","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359591","url":null,"abstract":"Traffic sign detection system is one of the most important part of self-driving cars. It is hard to correctly detect and classify the traffic signs because of the small scale property and the complexity of road environments. In this work, we propose a novel framework of feature transferring for traffic sign detection. We improve the traffic sign detection performance in the wild by transferring digit classifier's features to a detector. Specifically, we train a convolutional neural network(CNN) classifier on a digit training set, in which each image is cropped from the traffic sign detection dataset, and then use the classifier's high-level features as an additional supervision to the detector. With the help of the additional supervision, the detector can learn a better representation of traffic sign. Extensive experiments validate the effectiveness of our approach. Our method achieves state-of-the-art performance in traffic sign detection task on the largest traffic sign detection dataset, Tsinghua-Tencent 100K.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130336788","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}
Pub Date : 2017-12-01DOI: 10.1109/PIC.2017.8359506
Yan Zhao, Sujuan Liu
A path is rainbow if no two edges of it are colored the same. For a «-connected graph G and an integer k with 1 ≤ k ≤ κ, the rainbow k-connectivity rck (G) is the the minimum integer t for which there exists a t-edge-coloring of G such that for every two distinct vertices u and v of G, there exist at least k internally disjoint rainbow (u, v)-paths. This concept of rainbow k-connectivity, introduced by Chartrand et al., is a natural generalization of the rainbow connection number of a graph and has multiple applications in networks security. The Cartesian product of two graphs G and H, denoted by G□ H, is an important method to construct large graphs from small ones and plays a key role in design and analysis of networks. In this paper, we obtain some results for rainbow k-connectivity of Cartesian product graphs.
{"title":"Rainbow k-connectivity of some Cartesian product graphs","authors":"Yan Zhao, Sujuan Liu","doi":"10.1109/PIC.2017.8359506","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359506","url":null,"abstract":"A path is rainbow if no two edges of it are colored the same. For a «-connected graph G and an integer k with 1 ≤ k ≤ κ, the rainbow k-connectivity rck (G) is the the minimum integer t for which there exists a t-edge-coloring of G such that for every two distinct vertices u and v of G, there exist at least k internally disjoint rainbow (u, v)-paths. This concept of rainbow k-connectivity, introduced by Chartrand et al., is a natural generalization of the rainbow connection number of a graph and has multiple applications in networks security. The Cartesian product of two graphs G and H, denoted by G□ H, is an important method to construct large graphs from small ones and plays a key role in design and analysis of networks. In this paper, we obtain some results for rainbow k-connectivity of Cartesian product graphs.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116476750","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}
Pub Date : 2017-12-01DOI: 10.1109/PIC.2017.8359566
Junyan Zhao, Aixiang Wang
With the development of network technology, decision support and data mining has been widely applied in many fields, such as finance, marketing, quality analysis. But it isn't applied widely in the evaluation of network education. In order to improve the quality of personal training, universities regard the “the quality of teaching and teaching reform project” as the starting point, carry out teaching and management reform and explore the new talent cultivation mode. This paper summarizes the relative theories and methods of decision support, then introduces association rule in data mining. First, we analyze the classical association rules mining Apriori algorithm, then analyse this algorithm's disadvantages and improvement ways. Second, we use the Apriori algorithm, which can evaluate the network education from different aspects, thus providing manager with clear and actionable feedback to enhance their practice. Finally, the algorithm's efficiency is assessed and we points out the further research problems.
{"title":"Evaluation method and decision support of network education based on association rules","authors":"Junyan Zhao, Aixiang Wang","doi":"10.1109/PIC.2017.8359566","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359566","url":null,"abstract":"With the development of network technology, decision support and data mining has been widely applied in many fields, such as finance, marketing, quality analysis. But it isn't applied widely in the evaluation of network education. In order to improve the quality of personal training, universities regard the “the quality of teaching and teaching reform project” as the starting point, carry out teaching and management reform and explore the new talent cultivation mode. This paper summarizes the relative theories and methods of decision support, then introduces association rule in data mining. First, we analyze the classical association rules mining Apriori algorithm, then analyse this algorithm's disadvantages and improvement ways. Second, we use the Apriori algorithm, which can evaluate the network education from different aspects, thus providing manager with clear and actionable feedback to enhance their practice. Finally, the algorithm's efficiency is assessed and we points out the further research problems.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"24 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113958140","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}
Predicting the three-dimensional structure of a protein from its amino acid sequence is an important issue in the field of computational biology and bioinformatics. It remains as an unsolved problem and attract enormous researchers' interests. Different from most conventional methods, we model the protein structure prediction (PSP) problem as a multi-objective optimization problem. A three-objective energy function based on three physical terms is designed to evaluate a protein conformation. A multi-objective evolutionary strategy algorithm coupled with preference information is proposed in this study. The preference information is used in the survival criteria, focusing on the exploration of search process. The experimental results based on five proteins in PDB library demonstrate the effectiveness of proposed method. The analysis of Pareto fronts indicates that the preference information can make solutions diverse in genotypic space. Thus, the proposed method gives a new perspective for solving PSP problems.
{"title":"A preference-based multi-objective evolutionary strategy for Ab initio prediction of proteins","authors":"Zhenyu Song, Yajiao Tang, Xingqian Chen, Shuangbao Song, Shuangyu Song, Shangce Gao","doi":"10.1109/PIC.2017.8359505","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359505","url":null,"abstract":"Predicting the three-dimensional structure of a protein from its amino acid sequence is an important issue in the field of computational biology and bioinformatics. It remains as an unsolved problem and attract enormous researchers' interests. Different from most conventional methods, we model the protein structure prediction (PSP) problem as a multi-objective optimization problem. A three-objective energy function based on three physical terms is designed to evaluate a protein conformation. A multi-objective evolutionary strategy algorithm coupled with preference information is proposed in this study. The preference information is used in the survival criteria, focusing on the exploration of search process. The experimental results based on five proteins in PDB library demonstrate the effectiveness of proposed method. The analysis of Pareto fronts indicates that the preference information can make solutions diverse in genotypic space. Thus, the proposed method gives a new perspective for solving PSP problems.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122941642","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}
Pub Date : 2017-12-01DOI: 10.1109/PIC.2017.8359536
Wei Li, M. Ding
This paper proposed a tracking algorithm based on sparse coding and spectral residual saliency under the framework of particle filtering. The proposed algorithm can be divided into three parts. Firstly, spectral residual is used to calculate a saliency map of the current frame and then compute the saliency score of each particle. Secondly, several particles are eliminated directly based on the differences between the saliency scores of the particles in the current frame and the target score in the prior frame. Thirdly, ScSPM is used to compute the observation vector for the rest particles and the tracking task is finished in the framework of particle filtering. Both quantitative and qualitative experimental results demonstrate that the proposed algorithm performs favorably against the nine state-of-the-art trackers on ten challenging test sequences.
{"title":"Visual tracking via sparse coding and spectral residual","authors":"Wei Li, M. Ding","doi":"10.1109/PIC.2017.8359536","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359536","url":null,"abstract":"This paper proposed a tracking algorithm based on sparse coding and spectral residual saliency under the framework of particle filtering. The proposed algorithm can be divided into three parts. Firstly, spectral residual is used to calculate a saliency map of the current frame and then compute the saliency score of each particle. Secondly, several particles are eliminated directly based on the differences between the saliency scores of the particles in the current frame and the target score in the prior frame. Thirdly, ScSPM is used to compute the observation vector for the rest particles and the tracking task is finished in the framework of particle filtering. Both quantitative and qualitative experimental results demonstrate that the proposed algorithm performs favorably against the nine state-of-the-art trackers on ten challenging test sequences.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132943161","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}
Pub Date : 2017-12-01DOI: 10.1109/PIC.2017.8359594
Xie Shui-qing, Li Xiangyuan, L. Zhengyi, Zhou Hui, Yang Dandan
When carrying out special services of rescue and firefighting in buildings, underground works, tunnels and mine, where has no GPS signal, it's important to get location information of special staff, which used by guiding rescue, evacuation and force dispatch. In order to meet the above requirements, this system uses the inertial measurement unit constructed by 3-axis acceleration, 3-axis gyroscope and 3-axis geomagnetic sensor to complete the measurement of pedestrian motion information, calculate the personnel attitude through the cosine matrix, and use the extended Kalman filter the calculation of the speed and position of the personnel is carried out, and the zero speed detection is realized by the gyroscope to reduce the accumulated error of the calculation, thus realizing the key technology of inertial navigation. Using ZigBee and WIFI modules, the development of portable wireless network nodes, to build a wireless self-organizing network. Using embedded microcontrollers and MEMS inertial sensors to build a wearable wireless navigation and positioning system. Using wireless ad hoc network, implement real-time online monitoring of the staff positions and movement trajectory. The wearable wireless navigation and positioning system can accurately obtain the position and movement trajectory of the rescue personnel. Using the wireless ad hoc network, the position and the trajectory information of the rescue personnel can be transmitted to the control center in real time to provide information for the disaster relief command and decision support service.
{"title":"Design of low cost pedestrian location system based on inertial navigation","authors":"Xie Shui-qing, Li Xiangyuan, L. Zhengyi, Zhou Hui, Yang Dandan","doi":"10.1109/PIC.2017.8359594","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359594","url":null,"abstract":"When carrying out special services of rescue and firefighting in buildings, underground works, tunnels and mine, where has no GPS signal, it's important to get location information of special staff, which used by guiding rescue, evacuation and force dispatch. In order to meet the above requirements, this system uses the inertial measurement unit constructed by 3-axis acceleration, 3-axis gyroscope and 3-axis geomagnetic sensor to complete the measurement of pedestrian motion information, calculate the personnel attitude through the cosine matrix, and use the extended Kalman filter the calculation of the speed and position of the personnel is carried out, and the zero speed detection is realized by the gyroscope to reduce the accumulated error of the calculation, thus realizing the key technology of inertial navigation. Using ZigBee and WIFI modules, the development of portable wireless network nodes, to build a wireless self-organizing network. Using embedded microcontrollers and MEMS inertial sensors to build a wearable wireless navigation and positioning system. Using wireless ad hoc network, implement real-time online monitoring of the staff positions and movement trajectory. The wearable wireless navigation and positioning system can accurately obtain the position and movement trajectory of the rescue personnel. Using the wireless ad hoc network, the position and the trajectory information of the rescue personnel can be transmitted to the control center in real time to provide information for the disaster relief command and decision support service.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131993488","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}
Pub Date : 2017-12-01DOI: 10.1109/PIC.2017.8359582
Yange Dai, Lizhen Liu, Wei Song, Chao Du, Xinlei Zhao
The minimum size of the DataMatrix code is 0.0002 square inches and this size is the smallest of the current one-dimensional and two-dimensional codes. So it is particularly suitable for printing on metal parts of circuit boards. However, compared with the general two-dimensional code, there are still many technical difficulties on metal surface DataMatrix code identification technology. The reflection on metal surface is not conducive to the DataMatrix binarization. The large spacing between the codes is not conducive to positioning and identification. There is a distorted or incomplete DataMatrix code on metal surface. In this paper, a DataMatrix code recognition method is proposed by digital image processing technology. Firstly, Binarization is achieved by improving the traditional Otsu algorithm. The binarized image is dilated to solve the problem of large code interval. Secondly, the DataMatrix code region is located. The Hough transform is used to detect the four vertices of the DataMatrix code. The vertex is used to correct the twisty DataMatrix code. Finally, according to the structural characteristics of the DataMatrix code, the incomplete code is completed. According to the encoding rules, the DataMatrix code is decoded. After the above series of steps, we can achieve the purpose of identifying DataMatrix code.
{"title":"The realization of identification method for DataMatrix code","authors":"Yange Dai, Lizhen Liu, Wei Song, Chao Du, Xinlei Zhao","doi":"10.1109/PIC.2017.8359582","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359582","url":null,"abstract":"The minimum size of the DataMatrix code is 0.0002 square inches and this size is the smallest of the current one-dimensional and two-dimensional codes. So it is particularly suitable for printing on metal parts of circuit boards. However, compared with the general two-dimensional code, there are still many technical difficulties on metal surface DataMatrix code identification technology. The reflection on metal surface is not conducive to the DataMatrix binarization. The large spacing between the codes is not conducive to positioning and identification. There is a distorted or incomplete DataMatrix code on metal surface. In this paper, a DataMatrix code recognition method is proposed by digital image processing technology. Firstly, Binarization is achieved by improving the traditional Otsu algorithm. The binarized image is dilated to solve the problem of large code interval. Secondly, the DataMatrix code region is located. The Hough transform is used to detect the four vertices of the DataMatrix code. The vertex is used to correct the twisty DataMatrix code. Finally, according to the structural characteristics of the DataMatrix code, the incomplete code is completed. According to the encoding rules, the DataMatrix code is decoded. After the above series of steps, we can achieve the purpose of identifying DataMatrix code.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134179317","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}
Pub Date : 2017-12-01DOI: 10.1109/PIC.2017.8359546
Shaoming Zhu, Liancun Xiu, Yan Lu
The three-dimensional geological modeling and orebody visualization based on a small number of drilling cores are key issues for three-dimensional geological exploration. In this paper, we present an automatic pipeline of delineation and 3D profile mapping for potential exploration targets. As an integrated three-dimensional modeling process, the framework includes three key modules such as the terrain generation, delineation and three-dimensional profile mapping. The delineation is achieved by calculating the cutoff grade isosurface with a novel curved spline model. For the three-dimensional profile mapping, it is made by using the Kriging interpolation to generate the profile at an arbitrary angle within the delineation area. Finally, the proposed framework is validated by using the real mineral data of some drilling cores of Wulonggou area in Qinghai province of China, and the visualization results verify its effectiveness.
{"title":"An automatic pipeline of delineation and 3D profile mapping for potential exploration targets from mineral data of limited drilling cores","authors":"Shaoming Zhu, Liancun Xiu, Yan Lu","doi":"10.1109/PIC.2017.8359546","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359546","url":null,"abstract":"The three-dimensional geological modeling and orebody visualization based on a small number of drilling cores are key issues for three-dimensional geological exploration. In this paper, we present an automatic pipeline of delineation and 3D profile mapping for potential exploration targets. As an integrated three-dimensional modeling process, the framework includes three key modules such as the terrain generation, delineation and three-dimensional profile mapping. The delineation is achieved by calculating the cutoff grade isosurface with a novel curved spline model. For the three-dimensional profile mapping, it is made by using the Kriging interpolation to generate the profile at an arbitrary angle within the delineation area. Finally, the proposed framework is validated by using the real mineral data of some drilling cores of Wulonggou area in Qinghai province of China, and the visualization results verify its effectiveness.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"37 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133379224","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}
Pub Date : 2017-12-01DOI: 10.1109/PIC.2017.8359532
F. Zhu, Jiahang Liu, Tieqiao Chen
Imaging Interferometer (IIM) aboard Chang'E-1 is a Fourier transform imaging spectrometer, with goals to analyze the abundance and distribution of chemical elements on the lunar surface. IIM data suffer from various degradations, which will lead to misleading interpretations of IIM data and inaccuracy of subsequent applications. In this paper, we introduced a noise reduction method based on low-rank matrix decomposition theory. The restoration results are expected to have a better performance in image quality and spectral signatures according to visual and quantitative assessments. Meanwhile, we analyze the characteristic of the noise separated from IIM data using top spectral view of noise cube. The preliminary analysis of the noise characteristics contribute to optimize the data preprocessing of IIM data such as spectrum reconstruction and radiometric correction.
{"title":"Noise reduction and analysis for Chang'E-1 Imaging Interferometer (IIM) data","authors":"F. Zhu, Jiahang Liu, Tieqiao Chen","doi":"10.1109/PIC.2017.8359532","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359532","url":null,"abstract":"Imaging Interferometer (IIM) aboard Chang'E-1 is a Fourier transform imaging spectrometer, with goals to analyze the abundance and distribution of chemical elements on the lunar surface. IIM data suffer from various degradations, which will lead to misleading interpretations of IIM data and inaccuracy of subsequent applications. In this paper, we introduced a noise reduction method based on low-rank matrix decomposition theory. The restoration results are expected to have a better performance in image quality and spectral signatures according to visual and quantitative assessments. Meanwhile, we analyze the characteristic of the noise separated from IIM data using top spectral view of noise cube. The preliminary analysis of the noise characteristics contribute to optimize the data preprocessing of IIM data such as spectrum reconstruction and radiometric correction.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131623780","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}
Pub Date : 2017-12-01DOI: 10.1109/PIC.2017.8359538
Jie Shen, Zhe Chen, Cen Xu, Huibin Wang
Complicated optical scenes generally exist on the water surface. The noise originated from the light reflection seriously blocks the performance of the object detection method. This paper analyzes the correlation between the incident light angle and the flare noise, the relation between the solar altitude and the polarization state of the reflected light. Further, the correlation between the various imaging factors, such as the imaging time, the imaging angle of view, the polarization direction and the polarization state, is adjusted and optimized by the polarization imaging experiment. According to the experimental results, our polarization imaging method has good capability to suppress the noises generated by the light reflection, improving the accuracy of the object detection results.
{"title":"Polarization and solar altitude correlation analysis and application in object detection","authors":"Jie Shen, Zhe Chen, Cen Xu, Huibin Wang","doi":"10.1109/PIC.2017.8359538","DOIUrl":"https://doi.org/10.1109/PIC.2017.8359538","url":null,"abstract":"Complicated optical scenes generally exist on the water surface. The noise originated from the light reflection seriously blocks the performance of the object detection method. This paper analyzes the correlation between the incident light angle and the flare noise, the relation between the solar altitude and the polarization state of the reflected light. Further, the correlation between the various imaging factors, such as the imaging time, the imaging angle of view, the polarization direction and the polarization state, is adjusted and optimized by the polarization imaging experiment. According to the experimental results, our polarization imaging method has good capability to suppress the noises generated by the light reflection, improving the accuracy of the object detection results.","PeriodicalId":370588,"journal":{"name":"2017 International Conference on Progress in Informatics and Computing (PIC)","volume":"577 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115849893","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}
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