Cluster segmentation method for ancient architecture wall inscription contaminated writing brush character image

• Main Authors: WANG XIAOXIA, ZHAO YANXIA, LIU YINGJIE, JI LINNA, YANG FENGPU, LI DAWEI
• Format: Patent
• Language: English
• Published: 18.11.2015
• Subjects: CALCULATING; COMPUTING; COUNTING; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; PHYSICS

The invention discloses a cluster segmentation method for ancient architecture wall inscription contaminated writing brush character images, which belongs to the field of ancient architecture digital repair. The cluster segmentation method comprises the steps of: constructing a partial differential model for denoising an acquired image, and carrying out block-based enhancement according to illumination characteristics of the inscription image; segmenting the enhanced image by utilizing a maximum between-class variance method, and carrying out morphological processing on the image; carrying out regional positioning on the processed image to obtain minimum enclosing rectangles of character regions, and marking the corresponding character regions in the enhanced image; and finally, carrying out first FCM clustering on the character regions to determine a clustering central matrix, restraining a membership degree by utilizing an average grey degree similarity and a distance punishment function, and carrying out NKFCM clustering and deblurring processing to obtain a final cluster segmentation image. The cluster segmentation method can effectively eliminate influence of noise on clustering, can maintain the segmentation integrity, and can extract inscription characters with high quality. The cluster segmentation method is mainly used for clustering segmentation of ancient architecture wall inscription contaminated writing brush characters.