Zhongshuai Wang, Jiayu Huang, Yanhao Tang, Zhuo Shi, Rushi Lan
In order to improve the accuracy of indoor localization and the convenience of the user, This paper presents a fusion positioning algorithm using the local binary patterns’ feature approach to achieve ubiquitous and accurate positioning for smartphones and tablets. It is based on loosely coupling WiFi-based positioning and image analysis, This algorithm comprised of offline stage and online stage. On the offline stage, WiFi fingerprints were collected, and a fingerprint library sampled in different positions in the coordinate system was constructed. Photos were taken in that stage to extract the image features. On the online stage, the first filter process was to determine the possible area where the user is currently by using WiFi information captured in real-time. Then a distance compensation algorithm was proposed in this paper to extract features of the real-time image taken by the user to determine the exact localized position. Experimental results show that this algorithm can effectively improve localization precision compared with traditional WiFi and image based localization methods in environments with fewer APs (Access Points) and similar layouts, thus is capable for general localization or LBS (Location-Based Service) relevant applications.
{"title":"Indoor Location Fusion Algorithm Based on Smartphone","authors":"Zhongshuai Wang, Jiayu Huang, Yanhao Tang, Zhuo Shi, Rushi Lan","doi":"10.1109/ICDH.2018.00059","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00059","url":null,"abstract":"In order to improve the accuracy of indoor localization and the convenience of the user, This paper presents a fusion positioning algorithm using the local binary patterns’ feature approach to achieve ubiquitous and accurate positioning for smartphones and tablets. It is based on loosely coupling WiFi-based positioning and image analysis, This algorithm comprised of offline stage and online stage. On the offline stage, WiFi fingerprints were collected, and a fingerprint library sampled in different positions in the coordinate system was constructed. Photos were taken in that stage to extract the image features. On the online stage, the first filter process was to determine the possible area where the user is currently by using WiFi information captured in real-time. Then a distance compensation algorithm was proposed in this paper to extract features of the real-time image taken by the user to determine the exact localized position. Experimental results show that this algorithm can effectively improve localization precision compared with traditional WiFi and image based localization methods in environments with fewer APs (Access Points) and similar layouts, thus is capable for general localization or LBS (Location-Based Service) relevant applications.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129042930","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}
Sketch-based shape retrieval has received increasing attention in computer vision and computer graphics. It suffers from the challenge gap between 2D sketches and 3D shapes. In this paper, we propose a generalized similarity matching framework based on a multi-view attention network (MVAN), which can retrieve 3D shape that is most similar to the query sketch. In proposed approach, firstly we compute 2D projections of 3D shapes from multiple viewpoints and utilize a convolutional neural network to extract low level feature maps of these 2D projections. Secondly a multi-view attention network is designed to fuse the feature maps and forms a more accurate 3D shape representation. Meanwhile we use a CNN to extract the feature of sketches. Thirdly the similarity between sketches and 3D shapes is estimated via a generalized similarity model, which fuses some traditional similarity model into a generalized form and optimizes its parameters using a data-driven method. Finally we combine the MVAN and generalized similarity model into a unified network and train the model in an end-to-end manner. The experimental results on SHREC'13 and SHREC'14 sketch track benchmark datasets demonstrate that the proposed method can outperform state-of-the-art methods.
{"title":"Sketch-Based Shape Retrieval via Multi-view Attention and Generalized Similarity","authors":"Yongzhe Xu, Jiangchuan Hu, K. Zeng, Y. Gong","doi":"10.1109/ICDH.2018.00061","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00061","url":null,"abstract":"Sketch-based shape retrieval has received increasing attention in computer vision and computer graphics. It suffers from the challenge gap between 2D sketches and 3D shapes. In this paper, we propose a generalized similarity matching framework based on a multi-view attention network (MVAN), which can retrieve 3D shape that is most similar to the query sketch. In proposed approach, firstly we compute 2D projections of 3D shapes from multiple viewpoints and utilize a convolutional neural network to extract low level feature maps of these 2D projections. Secondly a multi-view attention network is designed to fuse the feature maps and forms a more accurate 3D shape representation. Meanwhile we use a CNN to extract the feature of sketches. Thirdly the similarity between sketches and 3D shapes is estimated via a generalized similarity model, which fuses some traditional similarity model into a generalized form and optimizes its parameters using a data-driven method. Finally we combine the MVAN and generalized similarity model into a unified network and train the model in an end-to-end manner. The experimental results on SHREC'13 and SHREC'14 sketch track benchmark datasets demonstrate that the proposed method can outperform state-of-the-art methods.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"91 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131672722","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}
Qianqian Deng, Ruomei Wang, Zixiao Gong, Guifeng Zheng, Zhuo Su
Research of the clothing recommendation algorithm is important that can be used to provide a more efficient method for consumers to select their expected clothing. Considering the characteristics of clothing product, in this paper, a personalized clothing recommendation algorithm based on fine-grained attributes is reported. In this method, the fine-grained attributes of the clothing are established based on clothing image. And a personalized clothing attributes preference model for each user combining with the fine-grained attributes of the clothing and personal parameters is built. This method is used in an application system based on client/server framework and a mobile phone software based on the Android platform.
{"title":"Research and Implementation of Personalized Clothing Recommendation Algorithm","authors":"Qianqian Deng, Ruomei Wang, Zixiao Gong, Guifeng Zheng, Zhuo Su","doi":"10.1109/ICDH.2018.00046","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00046","url":null,"abstract":"Research of the clothing recommendation algorithm is important that can be used to provide a more efficient method for consumers to select their expected clothing. Considering the characteristics of clothing product, in this paper, a personalized clothing recommendation algorithm based on fine-grained attributes is reported. In this method, the fine-grained attributes of the clothing are established based on clothing image. And a personalized clothing attributes preference model for each user combining with the fine-grained attributes of the clothing and personal parameters is built. This method is used in an application system based on client/server framework and a mobile phone software based on the Android platform.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115379838","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}
Focus on the problem that indoor location accuracy is generally low and various indoor location technologies are not widely used because some factors such as cost and accuracy. A data fusion method based on adaptive unscented Kalman filter (UKF) indoor location is proposed by analyzing the limitations of signal strength value (RSSI) fingerprint location, geomagnetic localization and inertial navigation location. The algorithm uses six-position error calibration method and Kalman filter to compensate the MEMS-SINS data, and establishes the correlation between location data and RSSI/geomagnetic data based on feature sorting vector fingerprint matching method. Finally, it is proposed to combine the adaptive factor with the unscented Kalman filter for data fusion, which improves the data stability and indoor location accuracy. The experimental results show that the adaptive UKF data fusion using MEMS-SINS/RSSI/geomagnetic data in the indoor environment can combine various advantages and achieve high-precision indoor location with an average absolute position error of 0.563m under the premise of low cost.
{"title":"A Data Fusion Method of Indoor Location Based on Adaptive UKF","authors":"Shouhua Wang, Dingmei Hu, Xiyan Sun, Suqing Yan, Jianhua Huang, Weimin Zhen, Yunke Li","doi":"10.1109/ICDH.2018.00052","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00052","url":null,"abstract":"Focus on the problem that indoor location accuracy is generally low and various indoor location technologies are not widely used because some factors such as cost and accuracy. A data fusion method based on adaptive unscented Kalman filter (UKF) indoor location is proposed by analyzing the limitations of signal strength value (RSSI) fingerprint location, geomagnetic localization and inertial navigation location. The algorithm uses six-position error calibration method and Kalman filter to compensate the MEMS-SINS data, and establishes the correlation between location data and RSSI/geomagnetic data based on feature sorting vector fingerprint matching method. Finally, it is proposed to combine the adaptive factor with the unscented Kalman filter for data fusion, which improves the data stability and indoor location accuracy. The experimental results show that the adaptive UKF data fusion using MEMS-SINS/RSSI/geomagnetic data in the indoor environment can combine various advantages and achieve high-precision indoor location with an average absolute position error of 0.563m under the premise of low cost.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116078378","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 information and communications technology (ICT) in education can effectively promote the development of ICT in subject by going to depth of a subject, and can practically assist a teaching process and improve the teaching quality. A dynamic mathematics intelligence education platform (DMIEP) is a tool of ICT in subject that goes to the depth of the mathematics subject. This thesis briefly reviews the development of the web-based dynamic mathematics software; proposes that design principles of the web-based, especially a mobile internet-based, DMIEP software should be "opening and sharing"; and provides goals to be achieved, such as seamless integration with a system or a third party application in a cross-terminal manner, good expansibility, and intelligence. Under the guidance of the principles and goals, an opening and sharing DMIEP has been designed and implemented, having functions such as relationship-based drawing, geometric graphic transformation, dynamic measurement, dynamics and parameters iteration, geometrical theorem automatic reasoning, and opening interfaces. At present, the platform has been widely used in the mathematics teaching process of primary and secondary schools.
{"title":"Design and Implementation of Web-Based Dynamic Mathematics Intelligence Education Platform","authors":"Hao Guan, Yongsheng Rao, Ying Wang, Xiaoxia Li, Ruxiang Chen","doi":"10.1109/ICDH.2018.00034","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00034","url":null,"abstract":"The information and communications technology (ICT) in education can effectively promote the development of ICT in subject by going to depth of a subject, and can practically assist a teaching process and improve the teaching quality. A dynamic mathematics intelligence education platform (DMIEP) is a tool of ICT in subject that goes to the depth of the mathematics subject. This thesis briefly reviews the development of the web-based dynamic mathematics software; proposes that design principles of the web-based, especially a mobile internet-based, DMIEP software should be \"opening and sharing\"; and provides goals to be achieved, such as seamless integration with a system or a third party application in a cross-terminal manner, good expansibility, and intelligence. Under the guidance of the principles and goals, an opening and sharing DMIEP has been designed and implemented, having functions such as relationship-based drawing, geometric graphic transformation, dynamic measurement, dynamics and parameters iteration, geometrical theorem automatic reasoning, and opening interfaces. At present, the platform has been widely used in the mathematics teaching process of primary and secondary schools.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"177 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114849670","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}
J. Nan, Xianyi Liao, Jie Chen, Xiangping Chen, J. Chen, Guang-hui Dong, Kangkang Liu, Gang Hu
Dengue fever is a kind of serious infectious disease associating with climate. It spreads in Guangzhou with numerous cases including mortality records over the last ten years. Thus, analyzing and predicting the dengue fever to avoid an dengue outbreak and reduce the personal safety loss is urgent and necessary. In this paper, we build a prediction model based on XGBoosst algorithm to explore the relationships between multiple climate factors (such as temperature, humidity, rainfall, etc.) and incidence of dengue fever. The encouraging experimental results demonstrate the feasibility and effectiveness of our prediction model.
{"title":"Using Climate Factors to Predict the Outbreak of Dengue Fever","authors":"J. Nan, Xianyi Liao, Jie Chen, Xiangping Chen, J. Chen, Guang-hui Dong, Kangkang Liu, Gang Hu","doi":"10.1109/ICDH.2018.00045","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00045","url":null,"abstract":"Dengue fever is a kind of serious infectious disease associating with climate. It spreads in Guangzhou with numerous cases including mortality records over the last ten years. Thus, analyzing and predicting the dengue fever to avoid an dengue outbreak and reduce the personal safety loss is urgent and necessary. In this paper, we build a prediction model based on XGBoosst algorithm to explore the relationships between multiple climate factors (such as temperature, humidity, rainfall, etc.) and incidence of dengue fever. The encouraging experimental results demonstrate the feasibility and effectiveness of our prediction model.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122056109","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}
T. Gu, Yanhao Tang, Zhongshuai Wang, Rushi Lan, Y. Zhong, Liang Chang
In order to meet the needs of complex indoor environment, it is important to develop more efficient solution to solve the problem of indoor positioning accuracy. In this paper, an indoor fusion positioning scheme is proposed, which uses Bluetooth, WIFI and ultra-wideband positioning for fusion and collaboration strategy, and uses the strategy of Heterogeneous network data fusion and the algorithm of similarity match to provide multi-source fusion indoor positioning. To evaluate our method, the experiments base of the Guilin Smart Industrial Park Incubation Center are achieved. The experiment results show that the indoor fusion positioning effect is greatly improved compared with the single positioning method, and the positioning error is significantly reduced.
{"title":"The Indoor Positioning Fusion Algorithm of Multi-source and Heterogeneous","authors":"T. Gu, Yanhao Tang, Zhongshuai Wang, Rushi Lan, Y. Zhong, Liang Chang","doi":"10.1109/ICDH.2018.00058","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00058","url":null,"abstract":"In order to meet the needs of complex indoor environment, it is important to develop more efficient solution to solve the problem of indoor positioning accuracy. In this paper, an indoor fusion positioning scheme is proposed, which uses Bluetooth, WIFI and ultra-wideband positioning for fusion and collaboration strategy, and uses the strategy of Heterogeneous network data fusion and the algorithm of similarity match to provide multi-source fusion indoor positioning. To evaluate our method, the experiments base of the Guilin Smart Industrial Park Incubation Center are achieved. The experiment results show that the indoor fusion positioning effect is greatly improved compared with the single positioning method, and the positioning error is significantly reduced.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126259277","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}
Ying Zhu, Li Zhou, Songhua Xu, Shanwen Guan, Rushi Lan, Xiyan Sun, Xiaonan Luo
The surface of the landslide in the Three Gorges Reservoir area has a "step-like" feature. Landslide displacement prediction method based on displacement response component model is one of the main methods for the prediction of landslide displacement. In order to solve problem about displacement prediction of Landslide fluctuation term in reservoirs, the reorganization and optimization of the main priming factors have not been considered yet. And a method for predicting landslide displacement HP-CEEMDAN-GA-ELM based on the reorganization and optimization of time-series CEEMDAN inducing factors has been proposed. Taking the surface displacement data of Baishuihe landslide from January 2008 to December 2012 as an example, the surface displacement time series is decomposed into the trend term displacement and the fluctuation term displacement by using HP filter. This trend item is predicted by GA-ELM. It decomposes predisposing factors through CEEMDAN, and uses gray correlation analysis to determine the optimal recombination factors for inducing factors. Based on Inducer component of reorganization, a GA-ELM model is established to predict the fluctuation term. Compared with multiple prediction models, the experimental results show that the prediction error of the model is small, which further prove the validity of the method.
{"title":"Displacement Prediction of Landslide Based on GA-ELM and Optimization of Inducing Factors","authors":"Ying Zhu, Li Zhou, Songhua Xu, Shanwen Guan, Rushi Lan, Xiyan Sun, Xiaonan Luo","doi":"10.1109/ICDH.2018.00039","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00039","url":null,"abstract":"The surface of the landslide in the Three Gorges Reservoir area has a \"step-like\" feature. Landslide displacement prediction method based on displacement response component model is one of the main methods for the prediction of landslide displacement. In order to solve problem about displacement prediction of Landslide fluctuation term in reservoirs, the reorganization and optimization of the main priming factors have not been considered yet. And a method for predicting landslide displacement HP-CEEMDAN-GA-ELM based on the reorganization and optimization of time-series CEEMDAN inducing factors has been proposed. Taking the surface displacement data of Baishuihe landslide from January 2008 to December 2012 as an example, the surface displacement time series is decomposed into the trend term displacement and the fluctuation term displacement by using HP filter. This trend item is predicted by GA-ELM. It decomposes predisposing factors through CEEMDAN, and uses gray correlation analysis to determine the optimal recombination factors for inducing factors. Based on Inducer component of reorganization, a GA-ELM model is established to predict the fluctuation term. Compared with multiple prediction models, the experimental results show that the prediction error of the model is small, which further prove the validity of the method.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"175 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132864954","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}
Yuanfa Ji, Yue Wu, Xiyan Sun, Suqing Yan, Qidong Chen, Baoqiang Du
In this paper a new algorithm for global navigation satellite system attitude determination based on CSO (Chicken Swarm Optimization) was developed. A distinct feature of this algorithm is the new optimization. The traditional LAMBDA algorithm for integer ambiguity resolution is time-consuming due to the large search space and complex calculation, so the attitude determination time is longer correspondingly. The optimization algorithm without search space based on least squares proposed in this paper improves the efficiency of fixing the integer ambiguity and applied to solve attitude problems. In conclusion, it is proven to work, offering a very efficient method of attitude determination.
{"title":"A New Algorithm for Attitude Detemination Based on Chicken Swarm Optimization","authors":"Yuanfa Ji, Yue Wu, Xiyan Sun, Suqing Yan, Qidong Chen, Baoqiang Du","doi":"10.1109/ICDH.2018.00030","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00030","url":null,"abstract":"In this paper a new algorithm for global navigation satellite system attitude determination based on CSO (Chicken Swarm Optimization) was developed. A distinct feature of this algorithm is the new optimization. The traditional LAMBDA algorithm for integer ambiguity resolution is time-consuming due to the large search space and complex calculation, so the attitude determination time is longer correspondingly. The optimization algorithm without search space based on least squares proposed in this paper improves the efficiency of fixing the integer ambiguity and applied to solve attitude problems. In conclusion, it is proven to work, offering a very efficient method of attitude determination.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130189622","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}
Xiyan Sun, Dong-Mei Liu, Yuanfa Ji, Suqing Yan, Chunhai Li, Baoqiang Du
Feature extraction in image encryption is a selective encryption method that has emerged in recent years. In this paper, significant detection is used to extract important information from the image, and we can pre-encrypt this information. The pre-encryption process uses an image block encryption algorithm based on Chen chaotic system and DNA coding. Secondly, the discrete wavelet transform (DWT) is used to encrypt the reference image. Finally, the pre-encrypted image is combined with transformed image which obtained from the reference image. After that, a visually meaningful encrypted image can obtain by inverse discrete wavelet transform. Because this final image is very similar to an ordinary image, it is not vulnerable to attack. This method effectively protects the plaintext image.
{"title":"A New Image Block Encryption Method Based on Chaotic Map and DNA Encoding","authors":"Xiyan Sun, Dong-Mei Liu, Yuanfa Ji, Suqing Yan, Chunhai Li, Baoqiang Du","doi":"10.1109/ICDH.2018.00015","DOIUrl":"https://doi.org/10.1109/ICDH.2018.00015","url":null,"abstract":"Feature extraction in image encryption is a selective encryption method that has emerged in recent years. In this paper, significant detection is used to extract important information from the image, and we can pre-encrypt this information. The pre-encryption process uses an image block encryption algorithm based on Chen chaotic system and DNA coding. Secondly, the discrete wavelet transform (DWT) is used to encrypt the reference image. Finally, the pre-encrypted image is combined with transformed image which obtained from the reference image. After that, a visually meaningful encrypted image can obtain by inverse discrete wavelet transform. Because this final image is very similar to an ordinary image, it is not vulnerable to attack. This method effectively protects the plaintext image.","PeriodicalId":117854,"journal":{"name":"2018 7th International Conference on Digital Home (ICDH)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115153027","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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