CAJ | 학술논문

根据木材缺陷图像识别技术的现状，针对适合识别木材各种表面缺陷图像的算法，对现有典型模型法进行图像识别方法的分析，提出了一种基于多个模型融合的木材表面缺陷图像快速识别算法。首先，在C－V模型中引入加权总变分能量（VTg（u）），使得二者分别能够与GAC模型连接，实现了在同一全局最小化框架下统一2种模型；然后采用全变分范数对偶化方法对模型进行了快速求解；最后给出了模型的数值化实现算法。结果表明：该算法不依赖初始轮廓线的选择，能够比较快速、准确地识别出木材的节子、孔洞、腐朽、空心等缺陷和单板多节子缺陷图像。
근거목재결함도상식별기술적현상，침대괄합식별목재각충표면결함도상적산법，대현유전형모형법진행도상식별방법적분석，제출료일충기우다개모형융합적목재표면결함도상쾌속식별산법。수선，재C－V모형중인입가권총변분능량（VTg（u）），사득이자분별능구여GAC모형련접，실현료재동일전국최소화광가하통일2충모형；연후채용전변분범수대우화방법대모형진행료쾌속구해；최후급출료모형적수치화실현산법。결과표명：해산법불의뢰초시륜곽선적선택，능구비교쾌속、준학지식별출목재적절자、공동、부후、공심등결함화단판다절자결함도상。
With the algorithms for all kinds of wood surface defect images , we analyzed image recognition method of the existing typical models, and put forward a fast recognition algorithm for wood defect images based on the multi -model fusion.First, the weighted total variation energy VTg(u) was introduced in ROF model and C-V model, so that two models could, re-spectively, connect with GAC model.Therefore, we achieved the unity of the three models in the same global minimization framework.And then, we used a dual formulation of TV norm to realize the fast minimization process .Finally, we provided the numerical algorithm of the model .Our algorithm does not depend on the choice of the initial contour , and it can quickly identify the outline of a variety of wood surface defects including the knots , holes, rot,hollow and veneer defect images with multiple knots .