林业科学
林業科學
임업과학
Scientia Silvae Sinicae
2015年
9期
90-95
,共6页
木材单板%节子%图像识别%图像分割%数学形态学%自动分等
木材單闆%節子%圖像識彆%圖像分割%數學形態學%自動分等
목재단판%절자%도상식별%도상분할%수학형태학%자동분등
wood veneer%knot%image recognition%image segmentation%mathematical morphology%automatic classification
【目的】提出一种基于数学形态学的木材单板节子识别改进算法,对木材单板表面节子进行快速识别和面积判断,旨在转化生产中由计算机智能控制自动分等代替人力分拣,提高木材单板分等效率。【方法】选取带有节子的木材单板为研究对象,以图像识别初步结果为基础,首先采集木材单板图像并进行灰度变换;然后根据灰度图像中节子和背景占据的不同灰度级范围,运用最大熵原理选择灰度阈值对图像进行分割,使节子从背景中初步分离出来;接着通过形态学运算去除各初选节子外部的干扰特征量,使节子外轮廓得以较准确显现;最后增加检出特征的外形轮廓判定,以防止板面可能存在的裂缝、污痕等其他特征量因颜色较深从背景中分离出来,被误检识别为节子。【结果】图像分割处理后节子周围存在的一些干扰特征量,通过形态学膨胀处理可切断干扰特征量和节子之间的联系,膨胀后继续进行腐蚀操作可保持节子真实大小,比较形态学开闭运算2种处理方法,形态学闭运算处理后节子更容易被识别出;检出的特征轮廓在进行椭圆拟合后辅以符合节子外形的条件限制可以提高识别精度,防止非节子被检出,其中通过计算特征轮廓点和拟合椭圆的匹配度大小可以初选是否符合节子特征,节子外形的条件限制主要用于过滤一些虽能拟合为椭圆但为长形物体比如裂隙等的影响。【结论】通过本项研究,可直观获取单板表面的节子数量和节子相对大小,其实际生产中使用硬件对接后,根据图像采集设备与待采集对象的相对位置、采集图像的分辨率等情况,结合系统判定结果可得出节子的真实大小,实现木材单板的自动分等。
【目的】提齣一種基于數學形態學的木材單闆節子識彆改進算法,對木材單闆錶麵節子進行快速識彆和麵積判斷,旨在轉化生產中由計算機智能控製自動分等代替人力分揀,提高木材單闆分等效率。【方法】選取帶有節子的木材單闆為研究對象,以圖像識彆初步結果為基礎,首先採集木材單闆圖像併進行灰度變換;然後根據灰度圖像中節子和揹景佔據的不同灰度級範圍,運用最大熵原理選擇灰度閾值對圖像進行分割,使節子從揹景中初步分離齣來;接著通過形態學運算去除各初選節子外部的榦擾特徵量,使節子外輪廓得以較準確顯現;最後增加檢齣特徵的外形輪廓判定,以防止闆麵可能存在的裂縫、汙痕等其他特徵量因顏色較深從揹景中分離齣來,被誤檢識彆為節子。【結果】圖像分割處理後節子週圍存在的一些榦擾特徵量,通過形態學膨脹處理可切斷榦擾特徵量和節子之間的聯繫,膨脹後繼續進行腐蝕操作可保持節子真實大小,比較形態學開閉運算2種處理方法,形態學閉運算處理後節子更容易被識彆齣;檢齣的特徵輪廓在進行橢圓擬閤後輔以符閤節子外形的條件限製可以提高識彆精度,防止非節子被檢齣,其中通過計算特徵輪廓點和擬閤橢圓的匹配度大小可以初選是否符閤節子特徵,節子外形的條件限製主要用于過濾一些雖能擬閤為橢圓但為長形物體比如裂隙等的影響。【結論】通過本項研究,可直觀穫取單闆錶麵的節子數量和節子相對大小,其實際生產中使用硬件對接後,根據圖像採集設備與待採集對象的相對位置、採集圖像的分辨率等情況,結閤繫統判定結果可得齣節子的真實大小,實現木材單闆的自動分等。
【목적】제출일충기우수학형태학적목재단판절자식별개진산법,대목재단판표면절자진행쾌속식별화면적판단,지재전화생산중유계산궤지능공제자동분등대체인력분간,제고목재단판분등효솔。【방법】선취대유절자적목재단판위연구대상,이도상식별초보결과위기출,수선채집목재단판도상병진행회도변환;연후근거회도도상중절자화배경점거적불동회도급범위,운용최대적원리선택회도역치대도상진행분할,사절자종배경중초보분리출래;접착통과형태학운산거제각초선절자외부적간우특정량,사절자외륜곽득이교준학현현;최후증가검출특정적외형륜곽판정,이방지판면가능존재적렬봉、오흔등기타특정량인안색교심종배경중분리출래,피오검식별위절자。【결과】도상분할처리후절자주위존재적일사간우특정량,통과형태학팽창처리가절단간우특정량화절자지간적련계,팽창후계속진행부식조작가보지절자진실대소,비교형태학개폐운산2충처리방법,형태학폐운산처리후절자경용역피식별출;검출적특정륜곽재진행타원의합후보이부합절자외형적조건한제가이제고식별정도,방지비절자피검출,기중통과계산특정륜곽점화의합타원적필배도대소가이초선시부부합절자특정,절자외형적조건한제주요용우과려일사수능의합위타원단위장형물체비여렬극등적영향。【결론】통과본항연구,가직관획취단판표면적절자수량화절자상대대소,기실제생산중사용경건대접후,근거도상채집설비여대채집대상적상대위치、채집도상적분변솔등정황,결합계통판정결과가득출절자적진실대소,실현목재단판적자동분등。
[Objective]Knot is an important evaluation index in the classification of wood veneer. The quantity of veneer knots and the maximum knot area can,to some extent,determine the grade of a wood veneer. Whereas by now, the classification of wood veneer processed in China mainly depends on visual inspection,which is of low efficiency. Therefore, quick identification and area assessment are performed to the surface knot of wood veneer with image recognition. Instead of artificial sorting is automatic classification by computer smart control,which can significantly promote the classification efficiency of wood veneer and is of great significance for the development and progress of wood industry. [Method]The wood veneer with knots are selected as object in this study. Bases on the preliminary results of image identification,an improved identification calculation for wood veneer knots using mathematical morphology is proposed. In order to solve the problem of missing characteristic quantity of partial knots or identification of non-knot characteristic quantity existing in the image identification of wood veneer,this work can be divided into 5 steps,those were,original image extraction,graying processing,image segmentation,margin inspection of characteristic quantity and knot identification. Firstly,images of wood veneer are collected,and grey level transformation is performed for the images for sequential image identification. Secondly,according to the knots in the gray images and different gray scope in the background,the image is split with the gray threshold chosen by the maximum entropy principle,so as to preliminarily separate the knots from the background. Then the interference characteristics outside the knots preliminarily selected are removed with morphological algorithm,thus the outer contour of knots can be accurately presented. Finally,outline assessment is performed for the characteristics detected,to prevent other factors such as crack and dirt being separated from the background due to their dark color and considered as knots. [Result]This study shows that,there are some interference characteristics around the knots after image segmentation,the relationship between interference characteristics and knots can be cut off by morphological expansion,and the corrosion operation after expansion can maintain the real size of knots. By comparing the morphological opening-and-closing operations, it is found that the knots processed by morphological closing operation can be more easily identified. The identification accuracy can be improved by performing ellipse fitting and outline condition restriction for the characteristic profile inspected,to prevent the identification of non-knots. Furthermore,knots can be preliminary assessed by calculating the characteristic profile points and the matching degree of ellipse,and the knots outline restriction is mainly used for filtering the influence of rectangular objects ( such as crack) that can be fitted into ellipse.[Conclusion]The knots quantity and relative size on the surface of wood veneer can be obtained by visual inspection,in the practical production processes,after interfacing with hardware,the real size of knots can be obtained according to the relative position of image collecting equipment and collecting objects and the resolution of images collected,etc. by combining the system assessment results,thus to realize the automatic classification of wood veneer.