Query Pixel Guided Stroke Extraction with Model-Based Matching for Offline Handwritten Chinese Characters

Wang, Tie-Qiang; Jiang, Xiaoyi; Liu, Cheng‐Lin

doi:10.1016/j.patcog.2021.108416

Cited by 9 publications

(14 citation statements)

References 37 publications

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“…The Chinese character skeleton applicable in IESCC should satisfy the four conditions: no redundant pixels, no redundant branches, no deformed skeleton and the skeleton conforms to the topology of the original character. To solve this problem, some machine learning based skeleton extraction algorithms [5][6][7][8][9][10][11][12] have been proposed. Yang et al [9] introduced a heuristic strategy, built on an extended theory of diagnostic assumptions, for extracting Ground Truth (GT) of object skeletons in binary shapes and natural images.…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Skeleton extraction of hard‐pen regular script based on stroke characterization and ambiguous zone detection

Xu,

Qin,

Xiong

et al. 2024

IET Image Processing

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The Intelligent Evaluation System for Calligraphy Characters (IESCC) is used for teaching calligraphy, and users can learn calligraphy through the modifications given by the system. Chinese character skeleton extraction is an important step in the intelligent evaluation algorithm of calligraphic characters. The skeletons of Chinese characters extracted by traditional refinement algorithms are prone to redundant branches and deformed skeletons, which can lead to skeleton extraction results that do not conform to the topology of the original character. In this study, the focus lies on hard‐pen regular script, and skeleton repair and extraction are performed for these characters. According to the writing characteristics of regular script, the redundant burs are removed and the deformation zone of the thinned skeleton is detected, and then the idea of first splitting is used, then restructuring, to propose a skeleton extraction algorithm based on stroke characterization and ambiguous zone detection for hard‐pen regular script, referred to as SCAD. First, a thinning algorithm is used to extract the skeleton of Chinese characters and remove redundant pixels. By analyzing the stroke characteristics of regular script, the burrs are classified and different conditions are set to detect and remove the burrs. Then the ambiguous zones are detected according to the different kinds of junction points. Then, curvature, stroke width and direction deviation are used to analyze the continuity of stroke segments, and the decision function is used to classify the stroke segments. Finally, the stroke segments with optimal pairings were compensated by interpolation according to the direction trend. This concludes the skeleton extraction. Skeleton extraction is performed on 1000 sample characters, and the SCAD algorithm can extract the skeleton of Chinese characters with an accuracy of up to 98.37%. It is proved that the SCAD method proposed here is a practical and effective method to extract the skeleton of hard‐pen regular script.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Skeleton extraction of hard‐pen regular script based on stroke characterization and ambiguous zone detection

Xu,

Qin,

Xiong

et al. 2024

IET Image Processing

View full text Add to dashboard Cite

show abstract

“…He [11] uses chain line segments to represent the boundaries of characters and separate interleaved strokes by detecting whether these boundaries are regular. To further improve the accuracy of stroke extraction, some template-based methods have been proposed [12,13]. Wang [13] use stroke structure matching to establish the correspondence between strokes and template strokes.…”

Section: Stroke Extraction For Chinese Charactermentioning

confidence: 99%

“…To further improve the accuracy of stroke extraction, some template-based methods have been proposed [12,13]. Wang [13] use stroke structure matching to establish the correspondence between strokes and template strokes. However, this method lacks the utilization of prior knowledge.…”

Section: Stroke Extraction For Chinese Charactermentioning

confidence: 99%

Intelligent Evaluation Method of Calligraphy Characters Based on Deep Stroke Extraction

2023

acss

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Calligraphy is an important part of Chinese culture. And calligraphy education is the main way to spread calligraphy culture. Intelligent calligraphy evaluation can reduce dependence on experienced calligraphy teachers and effectively enhance the development of calligraphy culture. However, traditional intelligent calligraphy evaluation methods mostly focus on the whole and lack fine-grained analysis, which cannot form effective evaluation results. In this paper, we propose an intelligent evaluation method for calligraphy characters based on deep stroke extraction. By disassembling calligraphy character strokes, a more fine-grained evaluation of the writing results of a single stroke can be achieved. This method consists of two main parts: stroke extraction module that extracts single strokes through a structure deformable image registration-based stroke extraction model; evaluation module that provides detailed quantitative evaluation results from the whole character, radicals and single strokes. The experimental results show that our method can extract strokes of complex calligraphy characters and provide detailed evaluation results of calligraphy characters effectively.

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“…Chinese character image decomposition, the most difficult but widely used method, has been studied by many researchers. Consequently, many methods were developed, such as corner detection algorithm [17, 18], point to boundary orientation distance of one triangular mesh [19], character library template matching segmentation [20, 21], B-spline curve matching [22], extraction of strokes using ambiguous zone information [18], extraction of strokes using optimum paths [11], stroke speed feature and stroke vector feature segmentation [23], etc. However, these methods require a lot of computation.…”

Section: Introductionmentioning

confidence: 99%

Image-based anti-interference robotic Chinese character writing system

Li,

Yang,

et al. 2024

Robotica

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This article designs a robotic Chinese character writing system that can resist random human interference. Firstly, an innovative stroke extraction method of Chinese characters was devised. A basic Chinese character stroke extraction method based on cumulative direction vectors is used to extract the components that make up the strokes of Chinese characters. The components are then stitched together into strokes based on the sequential base stroke joining method. To enable the robot to imitate handwriting Chinese character skills, we utilised stroke information as the demonstration and modelled the skills using dynamic movement primitives (DMPs). To suppress random human interference, this article combines improved DMPs and conductance control to adjust robot trajectories based on real-time visual measurements. The experimental results show that the proposed method can accurately extract the strokes of most Chinese characters. The designed trajectory adjustment method offers better smoothness and robustness than direct rotating and translating curves. The robot is able to adjust its posture and trajectory in real time to eliminate the negative impacts of human interference.

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Query Pixel Guided Stroke Extraction with Model-Based Matching for Offline Handwritten Chinese Characters

Cited by 9 publications

References 37 publications

Skeleton extraction of hard‐pen regular script based on stroke characterization and ambiguous zone detection

Skeleton extraction of hard‐pen regular script based on stroke characterization and ambiguous zone detection

Intelligent Evaluation Method of Calligraphy Characters Based on Deep Stroke Extraction

Image-based anti-interference robotic Chinese character writing system

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