CAJ | 학술논문

为了准确地识别原木端面轮廓，建立了联合像素特征和边缘结构的成捆原木轮廓识别模型，引入支持向量机改进原木端面像素点的识别效果，并用最小二乘法对边缘轮廓进行圆拟合。实验结果表明，在图像背景、原木端面都不理想的情况下，该方法能较为有效地完成成捆原木端面轮廓识别。
위료준학지식별원목단면륜곽，건립료연합상소특정화변연결구적성곤원목륜곽식별모형，인입지지향량궤개진원목단면상소점적식별효과，병용최소이승법대변연륜곽진행원의합。실험결과표명，재도상배경、원목단면도불이상적정황하，해방법능교위유효지완성성곤원목단면륜곽식별。
A model of outline eztraction of bundled logs cross section based upon pizel feature and edge structure is developed to improve bundled logs image processing. A support vector machine(SVM)is used to eztract the pizels of cross section of logs,and the least square method is applied to fit the circle of edge pizels. Finally,outlines of bundled logs are eztracted. The obtained results of ezperiment demonstrate the validity of the proposed method in the case of the cross section of logs is not the ideal smooth and the background is complez.