5 results about "Stroke width" patented technology

A method for extracting key contour points of Chinese characters based on key skeleton points and stroke width belongs to the field of computer and Chinese character vectorization, which comprises the following steps: inputting a single Chinese character picture, performing pretreatment to generate a binary image; extracting the skeleton of the Chinese character by using a skeleton extraction algorithm; further extracting key skeleton points of the Chinese character; obtaining the stroke width at each key skeleton point of the Chinese character; obtaining the contour points of the Chinese character by using a contour extraction algorithm; sequentially traversing all contour points of the Chinese character, calculating the distance from the current contour point to the nearest key skeleton point, calculating the distance threshold of the current nearest key skeleton point, judging whether the current contour point is a key contour point by comparing the distance from the current contour point to the nearest key skeleton point with the distance threshold, and recording the current contour point as a key contour point if the distance is less than the distance threshold. The application effectively improves the quality of Chinese character vectorization, maintains all detail features, effectively removes noise contour points and redundant contour points, and reduces the storage space size of the vectorized Chinese characters.

This invention discloses a method for detecting and recognizing tilted and distorted text in natural scenes, comprising the following steps: preprocessing a natural scene image containing tilted, curved, or perspective-distorted text, and obtaining the stroke width information of each pixel in the image and the corresponding edge pixel relationship through edge detection and stroke width calculation. Based on the consistency of stroke width and the edge correspondence, connected region aggregation is performed on the pixels in the image to obtain candidate text regions, and a text stroke structure is constructed. The stroke center lines are further extracted and control points are generated. The weights of the control points are determined based on the stroke structure information, and a weighted control point set is constructed. Based on this control point set and candidate regions, a deformation mapping is generated using the moving least squares method to correct the tilted and distorted text. The corrected text regions are then filtered and character recognition is performed, outputting the text detection and recognition results. This invention is applicable to text processing in complex backgrounds.

This invention relates to the field of vision and image processing technology, and discloses a text compliance detection method based on image semantic segmentation. The method acquires and grayscales a text image, obtains an initial mask through semantic segmentation, calculates the local pixel mean drift coefficient, and determines the dynamic edge search bandwidth accordingly. Within the bandwidth, it statistically analyzes the magnitude and distribution characteristics of the first-order spatial gradient, calculates the rectified edge probability score of the target pixel, constructs a topological gravitational potential energy using the probability score as the gravity source, calculates the adhesion blocking coefficient by solving the Hessian matrix determinant and combining it with the global drift variance, then extracts the potential energy maximum point as the stroke center, extracts the cross-section along the potential surface normal, performs weighted integration, and calculates the equivalent stroke width. Finally, it calculates the width dispersion and combines it with the global drift mean to calculate the compliance discrimination coefficient, outputting the detection result. This technical solution effectively overcomes semantic drift and false edge traps, and accurately decouples local ink topological adhesion.

The application discloses a method for extracting key skeleton points of Chinese characters based on multi-scale, and belongs to the field of computer and Chinese character vectorization. The method comprises the following steps: inputting a single Chinese character picture, and performing pretreatment to generate a binary image; extracting the skeleton of the Chinese character by using a skeleton extraction algorithm; extracting all end points and all intersection points of the skeleton based on the aggregation degree; extracting all inflection points of the skeleton by using a small-scale filtering method; extracting all bending points of the skeleton by using a large-scale filtering method; further extracting all width change points of the average stroke width; and recording all the end points, intersection points, inflection points, bending points and width change points as all key skeleton points of the Chinese character. The application can effectively extract the key skeleton points of all changes of the Chinese character, effectively reduce the number of non-key skeleton points, and thus effectively reduce the storage space size of the vectorized Chinese character under the premise of ensuring the high quality of the vectorized Chinese character.

The invention discloses an open type soft pen calligraphy character three-fork skeleton precise segmentation method based on position classification, and relates to the technical field of calligraphy digital processing, and the method comprises the steps: carrying out the binary preprocessing of a soft pen calligraphy image, obtaining a Chinese character skeleton through a Zhang-Suen refinement algorithm, and defining a three-fork angular point and a three-fork skeleton; dividing the multi-structure Chinese character into a single structure, and classifying according to the number and position distribution of three-fork skeleton points in the single structure; and finally, for a single structure of one, two or more than three trifurcate skeleton points, combining parameters such as skeleton path length, tangent value and the like to formulate a differential segmentation and retention rule. The method adapts to the stroke width change characteristics of soft pen calligraphy, solves the problems of stroke splitting and skeleton reconnection in a traditional method, assists the robot in track adjustment, realizes smooth stroke transition, and improves the copying precision.