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"Calligraphy Data processing."
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Human Machine Interface with Wearable Electronics Using Biodegradable Triboelectric Films for Calligraphy Practice and Correction
HighlightsA wearable triboelectric nanogenerator (denoted as CSF-TENG) is designed using biodegradable and carboxymethyl chitosan-silk fibroin (CSF) film.In vitro biodegradation of CSF film is performed through trypsin and lysozyme. 63.1% of CSF film is removed by trypsin and lysozyme after degrading for 11 days.An intuitive writing system is designed by CSF-TENGs-based human-machine interface to promptly track writing steps, highlight the stroke in advance, and access the accuracy of letters.Letter handwriting, especially stroke correction, is of great importance for recording languages and expressing and exchanging ideas for individual behavior and the public. In this study, a biodegradable and conductive carboxymethyl chitosan-silk fibroin (CSF) film is prepared to design wearable triboelectric nanogenerator (denoted as CSF-TENG), which outputs of Voc ≈ 165 V, Isc ≈ 1.4 μA, and Qsc ≈ 72 mW cm−2. Further, in vitro biodegradation of CSF film is performed through trypsin and lysozyme. The results show that trypsin and lysozyme have stable and favorable biodegradation properties, removing 63.1% of CSF film after degrading for 11 days. Further, the CSF-TENG-based human–machine interface (HMI) is designed to promptly track writing steps and access the accuracy of letters, resulting in a straightforward communication media of human and machine. The CSF-TENG-based HMI can automatically recognize and correct three representative letters (F, H, and K), which is benefited by HMI system for data processing and analysis. The CSF-TENG-based HMI can make decisions for the next stroke, highlighting the stroke in advance by replacing it with red, which can be a candidate for calligraphy practice and correction. Finally, various demonstrations are done in real-time to achieve virtual and real-world controls including writing, vehicle movements, and healthcare.
Journal Article
Calliar: an online handwritten dataset for Arabic calligraphy
Calligraphy is an essential part of the Arabic heritage and culture. It has been used in the past for the decoration of houses and mosques. Usually, such calligraphy is designed manually by experts with aesthetic insights. In the past few years, there has been a considerable effort to digitize such type of art by either taking a photograph of decorated buildings or drawing them using digital devices. The latter is considered an online form where the drawing is tracked by recording the apparatus movement, an electronic pen, for instance, on a screen. In the literature, there are many offline datasets with diverse Arabic styles for calligraphy. However, there is no available online dataset for Arabic calligraphy. In this paper, we illustrate our approach for collecting and annotating an online dataset for Arabic calligraphy called Calliar, which consists of 2,500 sentences. Calliar is annotated for stroke, character, word, and sentence-level prediction. We also propose various baseline models for the character classification task. The results we achieved highlight that it is still an open problem.
Journal Article
Recognition method for stone carved calligraphy characters based on a convolutional neural network
Chinese calligraphy is an important part of Chinese national culture and art and part of the essence of Chinese national culture. Stone calligraphy is one of the important elements of Chinese calligraphy art. Stone carved calligraphy characters have high cultural and artistic value. Therefore, accurately recognizing stone carved calligraphy characters are of great importance. Stone carved calligraphy can identify hard-to-preserve stone calligraphy paper materials in electronic data that can be preserved for a long time, thereby offering important reference materials for the study of the historical development of Chinese calligraphy art. Moreover, with the development of science and technology and the investment of China in cultural and artistic undertakings, computer-aided calligraphy character recognition technology is also constantly improving, and its application in calligraphy recognition is becoming increasingly extensive. This article aims to study a method of stone inscription calligraphy recognition based on convolutional neural networks. In this paper, we use an image recognition and optimization method consisting of a convolutional neural network to carry out an experiment with stone inscription calligraphy characters. It was concluded that the recognition accuracy of stone calligraphy characters by the convolutional neural network reached 99.2%, indicating that this stone calligraphy character recognition method based on a convolutional neural network has a good ability to recognize stone calligraphy characters.
Journal Article
A novel generative adversarial net for calligraphic tablet images denoising
Chinese calligraphic images have important historical and artistic value, but natural weathering and man-made decay severely damage these works, thus image denoising is an important topic to be addressed. Traditional denoising methods still leave room for improvement. In this paper, image denoising is modeled as generation of clean image by using GAN (Goodfellow I et al. Advances in Neural Information Processing Systems 2672–2680, 2014) with an embedment of residual dense blocks (Zhang Y et al. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018) that was formerly used for super resolution reconstruction. Meanwhile, a new type of noise is defined to simulate the real noise, and is used for compensation of unpaired data in the training set for GAN. The new structure, used with some preprocessing and training methods, yield satisfactory results compared to known denoising methods.
Journal Article
Development of ancient Chinese inscription rubbings knowledge base in the context of cultural communication and art appreciation
PurposeTo promote the cultural communication and art appreciation of Inscriptions and calligraphy which are important cultural heritages in China, with a broad crowd base and educational appreciation value, by using digital humanities methods and technologies, the paper aims to discuss how to develop a new user-oriented knowledge base according to user needs for inscription rubbings research and appreciation.Design/methodology/approachThe paper investigates user needs and current problems on the basis of status quo and summation of extensive service experience; validates the rationality of requirements and user scenarios with user research methods including focus groups, interviews and behavior observations; then designs and develops the technical solution of data process, knowledge base construction and service platform through experimental research methods based on agile project management.FindingsThe paper proposes a new reading mode for browsing and appreciation inscription rubbing works, a diverse knowledge-integrated knowledge organizational structure, a systematic user experience and service guiding framework which can be widely applicable to the development of other cultural heritage knowledge bases. Apart from that, the paper puts forward intelligent service development goals for the future.Originality/valueThe paper proposes a new reading mode with the overall functions and user experience design and development for browsing and appreciation inscription rubbing works, a diverse knowledge-integrated knowledge organizational structure, a systematic user experience and service guiding framework which can be widely applicable to the development of other cultural heritage knowledge bases. Apart from that, the paper puts forward intelligent service development goals for the future.
Journal Article
ACPAS: an expert-assistance system for authenticating ancient Chinese paintings via LLM-based agents
Authentication of ancient Chinese paintings is crucial to protecting and preserving cultural heritage. However, traditional authentication methods rely heavily on expert knowledge and experience, and are difficult to handle unstructured and multimodal information. In addition, the lack of interactive tools also hinders humanities scholars from effectively applying advanced technologies. In this study, we present ACPAS, an intelligent authentication system that enables an expert-led, AI-assisted authentication model. The system uses Large Language models (LLMs) to interpret the needs of experts and assigns them to the corresponding tool modules for processing. It integrates image processing, text retrieval, and structured databases, and employs interactive visualizations to support reasoning. Case studies and user evaluations demonstrate that ACPAS improves efficiency and results in interpretability. It provides a new paradigm for cultural heritage protection and digital humanities research and promotes the deep integration of artificial intelligence and humanities.
Journal Article
A de-noising method based on L0 gradient minimization and guided filter for ancient Chinese calligraphy works on steles
A clear stele image of ancient Chinese calligraphy pieces is very useful for studying ancient Chinese calligraphy. However, due to hundreds of or even thousands of years of natural or artificial damage on stele, images of ancient Chinese stele calligraphy works usually suffer from a large amount of image noise, and which usually leads to a poor visibility. To address this problem, in this paper, we propose a de-noising method based on L0 gradient minimization and guided filter. It consists of two main operations in sequence: First, L0 gradient minimization is utilized to obtain a random-noise free map, and then the random-noise free map is used as a guided image, and convoluted with its corresponding original noised stele image by a guided filter to obtain an edge preserved random-noise free image. Finally, the eight-connection region-based de-noising technique is followed to remove ant-like isolated blocks. Experiments demonstrate that the proposed method is superior to several recent published stele image de-noising techniques in terms of preserving the character structures.
Journal Article
An integrated method for ancient Chinese tablet images de-noising based on assemble of multiple image smoothing filters
There are unavoidably lots of noises in tablet images due to natural or man-made decay, which have a significant affect on learning and studying of the ancient Chinese calligraphy works with Chinese tablet images. To address this problem, an integrated de-noising method, based on assemble of multiple image smoothing filters, is proposed in this paper. To avoid damaging characters and losing detail information, input Chinese tablet images are enhanced by the Guided filter and multi-scale Retinex filter firstly. Then the enhanced tablet images are converted to binary ones by the Otsu thresholding filter. Finally, most random and block noises are removed using an improved scan-length statistics filter based on connected region. The performance of the proposed method was validated on our Chinese tablet image data set, which consists of 200 Chinese tablet images with different kinds of noise. Experiments show that, the proposed method can effectively remove most image noise (including various block noise, linear noise and ant-like noise) and preserve characters better than existing methods.
Journal Article
A study on a content-based image retrieval technique for Chinese paintings
Purpose
The purpose of this study is to build a database of digital Chinese painting images and use the proposed technique to extract image and texture information, and search images similar to the query image based on colour histogram and texture features in the database. Thus, retrieving images by this image technique is expected to make the retrieval of Chinese painting images more precise and convenient for users.
Design/methodology/approach
In this study, a technique is proposed that considers spatial information of colours in addition to texture feature in image retrieval. This technique can be applied to retrieval of Chinese painting images. A database of 1,200 digital Chinese painting images in three categories was built, including landscape, flower and figure. The authors develop an image-retrieval technique that considers colour distribution, spatial information of colours and texture.
Findings
In this study, a database of 1,200 digital Chinese painting images in three categories was built, including landscape, flower and figure. An image-retrieval technique was developed that considers colour distribution, spatial information of colours and texture. Through adjustment of feature values, this technique is able to process both landscape and portrait images. This technique also addresses liubai (i.e. blank) and text problems in the images. The experimental results confirm high precision rate of the proposed retrieval technique.
Originality/value
In this paper, a novel Chinese painting image-retrieval technique is proposed. Existing image-retrieval techniques and the features of Chinese painting are used to retrieve Chinese painting images. The proposed technique can exclude less important image information in Chinese painting images for instance liubai and calligraphy while calculating the feature values in them. The experimental results confirm that the proposed technique delivers a retrieval precision rate as high as 92 per cent and does not require a considerable computing power for feature extraction. This technique can be applied to Web page image retrieval or to other mobile applications.
Journal Article