The art of inscriptions is one of the most important components of the glorious ancient culture in China.It is an essential method not only for ancients to record history and disseminate culture but also to provide or...The art of inscriptions is one of the most important components of the glorious ancient culture in China.It is an essential method not only for ancients to record history and disseminate culture but also to provide original written and pictorial records for subsequent generations to learn about ancient Chinese culture.However,the art of inscriptions and calligraphy is currently not widely available because of its professional chirography,style and composition.Moreover,traditional calligraphy exhibitions cannot provide the public with an interactive and intuitive way to present the features of Chinese characters,such as stroke thickness.Therefore,in this paper,we present an interactive visual system to support the public in understanding and appreciating the calligraphic style of the inscriptions of the Tang Dynasty and the evolutionary path of the calligraphic style of Wang Xizhi.Wefirst employ image processing technology to extract calligraphy features.Then,we help users explore the development of calligraphy from the spatial-temporal dimension and analyze the similarity between the works at two granularity levels:Chinese character structure and the works’style.Furthermore,the system also provides a metaphorical visualization method to enhance the concretization of calligraphic appreciation.Case studies and comprehensive evaluation demonstrate the usability of our proposed visual analysis system of the calligraphic style of the inscriptions in the Tang Dynasty.展开更多
Machine vision measurement(MVM)is an essential approach that measures the area or length of a target efficiently and non-destructively for product quality control.The result of MVM is determined by its configuration,e...Machine vision measurement(MVM)is an essential approach that measures the area or length of a target efficiently and non-destructively for product quality control.The result of MVM is determined by its configuration,especially the lighting scheme design in image acquisition and the algorithmic parameter optimization in image processing.In a traditional workflow,engineers constantly adjust and verify the configuration for an acceptable result,which is time-consuming and significantly depends on expertise.To address these challenges,we propose a target-independent approach,visual interactive image clustering,which facilitates configuration optimization by grouping images into different clusters to suggest lighting schemes with common parameters.Our approach has four steps:data preparation,data sampling,data processing,and visual analysis with our visualization system.During preparation,engineers design several candidate lighting schemes to acquire images and develop an algorithm to process images.Our approach samples engineer-defined parameters for each image and obtains results by executing the algorithm.The core of data processing is the explainable measurement of the relationships among images using the algorithmic parameters.Based on the image relationships,we develop VMExplorer,a visual analytics system that assists engineers in grouping images into clusters and exploring parameters.Finally,engineers can determine an appropriate lighting scheme with robust parameter combinations.To demonstrate the effiectiveness and usability of our approach,we conduct a case study with engineers and obtain feedback from expert interviews.展开更多
基金supported by Zhejiang Provincial Natural Science Foundation of China(No.LR23F020003)National Natural Science Foundation of China(Nos.61972356 and 62036009).
文摘The art of inscriptions is one of the most important components of the glorious ancient culture in China.It is an essential method not only for ancients to record history and disseminate culture but also to provide original written and pictorial records for subsequent generations to learn about ancient Chinese culture.However,the art of inscriptions and calligraphy is currently not widely available because of its professional chirography,style and composition.Moreover,traditional calligraphy exhibitions cannot provide the public with an interactive and intuitive way to present the features of Chinese characters,such as stroke thickness.Therefore,in this paper,we present an interactive visual system to support the public in understanding and appreciating the calligraphic style of the inscriptions of the Tang Dynasty and the evolutionary path of the calligraphic style of Wang Xizhi.Wefirst employ image processing technology to extract calligraphy features.Then,we help users explore the development of calligraphy from the spatial-temporal dimension and analyze the similarity between the works at two granularity levels:Chinese character structure and the works’style.Furthermore,the system also provides a metaphorical visualization method to enhance the concretization of calligraphic appreciation.Case studies and comprehensive evaluation demonstrate the usability of our proposed visual analysis system of the calligraphic style of the inscriptions in the Tang Dynasty.
基金Project supported by the National Key R&D Program of China(No.2020YFB1707700)the Zhejiang Provincial Natural Science Foundation of China(No.LR23F020003)the National Nat-ural Science Foundation of China(Nos.61972356 and 62036009)。
文摘Machine vision measurement(MVM)is an essential approach that measures the area or length of a target efficiently and non-destructively for product quality control.The result of MVM is determined by its configuration,especially the lighting scheme design in image acquisition and the algorithmic parameter optimization in image processing.In a traditional workflow,engineers constantly adjust and verify the configuration for an acceptable result,which is time-consuming and significantly depends on expertise.To address these challenges,we propose a target-independent approach,visual interactive image clustering,which facilitates configuration optimization by grouping images into different clusters to suggest lighting schemes with common parameters.Our approach has four steps:data preparation,data sampling,data processing,and visual analysis with our visualization system.During preparation,engineers design several candidate lighting schemes to acquire images and develop an algorithm to process images.Our approach samples engineer-defined parameters for each image and obtains results by executing the algorithm.The core of data processing is the explainable measurement of the relationships among images using the algorithmic parameters.Based on the image relationships,we develop VMExplorer,a visual analytics system that assists engineers in grouping images into clusters and exploring parameters.Finally,engineers can determine an appropriate lighting scheme with robust parameter combinations.To demonstrate the effiectiveness and usability of our approach,we conduct a case study with engineers and obtain feedback from expert interviews.
