农业工程学报
農業工程學報
농업공정학보
2014年
9期
249-255
,共7页
王芳%文友先%谭佐军%程飞%魏薇%李治%易伟松
王芳%文友先%譚佐軍%程飛%魏薇%李治%易偉鬆
왕방%문우선%담좌군%정비%위미%리치%역위송
无损检测%极化%图像处理%裂纹%皮蛋%斯托克斯矢量%聚类算法
無損檢測%極化%圖像處理%裂紋%皮蛋%斯託剋斯矢量%聚類算法
무손검측%겁화%도상처리%렬문%피단%사탁극사시량%취류산법
nondestructive examination%polarization%image processing%crack%preserved egg%the Stokes Vector%clustering algorithm
检测出缸皮蛋蛋壳是否有裂纹是确保皮蛋质量的重要环节。腌制好的皮蛋蛋壳表面大量的灰褐色斑点和一些大块黑斑使得其蛋壳表面的裂纹不易检测。皮蛋表壳斑点和裂纹的微细结构不同,对偏振光的退偏程度也不一样,可以利用皮蛋表壳各点偏振度的差异来识别其裂纹。该文设计了皮蛋表壳偏振图像采集系统,基于皮蛋0、45°、90°、-45°4个偏振角度的图像和斯托克斯公式获得皮蛋表壳裂纹的偏振度图像,对偏振图像进行阈值预处理后,以皮蛋表壳偏振图像中像素最高且连通区域最大部分作为中心,截取100×100像素的图像,提取该图像裂纹长度、均方比、偏度和峰度等4个特征参数,采用Kmeans聚类分析算法准确识别了皮蛋表壳裂纹。试验证明,该方法综合准确率为93%,其中好壳皮蛋识别准确率为100%,裂纹蛋识别准确率为88.3%,这表明偏振光检测技术能有效地识别皮蛋蛋壳裂纹。
檢測齣缸皮蛋蛋殼是否有裂紋是確保皮蛋質量的重要環節。醃製好的皮蛋蛋殼錶麵大量的灰褐色斑點和一些大塊黑斑使得其蛋殼錶麵的裂紋不易檢測。皮蛋錶殼斑點和裂紋的微細結構不同,對偏振光的退偏程度也不一樣,可以利用皮蛋錶殼各點偏振度的差異來識彆其裂紋。該文設計瞭皮蛋錶殼偏振圖像採集繫統,基于皮蛋0、45°、90°、-45°4箇偏振角度的圖像和斯託剋斯公式穫得皮蛋錶殼裂紋的偏振度圖像,對偏振圖像進行閾值預處理後,以皮蛋錶殼偏振圖像中像素最高且連通區域最大部分作為中心,截取100×100像素的圖像,提取該圖像裂紋長度、均方比、偏度和峰度等4箇特徵參數,採用Kmeans聚類分析算法準確識彆瞭皮蛋錶殼裂紋。試驗證明,該方法綜閤準確率為93%,其中好殼皮蛋識彆準確率為100%,裂紋蛋識彆準確率為88.3%,這錶明偏振光檢測技術能有效地識彆皮蛋蛋殼裂紋。
검측출항피단단각시부유렬문시학보피단질량적중요배절。업제호적피단단각표면대량적회갈색반점화일사대괴흑반사득기단각표면적렬문불역검측。피단표각반점화렬문적미세결구불동,대편진광적퇴편정도야불일양,가이이용피단표각각점편진도적차이래식별기렬문。해문설계료피단표각편진도상채집계통,기우피단0、45°、90°、-45°4개편진각도적도상화사탁극사공식획득피단표각렬문적편진도도상,대편진도상진행역치예처리후,이피단표각편진도상중상소최고차련통구역최대부분작위중심,절취100×100상소적도상,제취해도상렬문장도、균방비、편도화봉도등4개특정삼수,채용Kmeans취류분석산법준학식별료피단표각렬문。시험증명,해방법종합준학솔위93%,기중호각피단식별준학솔위100%,렬문단식별준학솔위88.3%,저표명편진광검측기술능유효지식별피단단각렬문。
Pickled egg had lots of beige spots and some large black spots on its eggshell, so it is difficult to detect cracks on the preserved eggshell. A polarization optical system was designed to obtain images, and the system was tested by the Malus law. Polarization optical system was used to acquire images on different polarization angles, including 0, 45°,-45°and 90°, and then the Stokes images and polarization images were processed by image fusion technique with the Stokes Formula. According to different depolarization mechanisms for black spots and cracks on preserved eggshell, it can distinguish black spots and cracks on the polarization image. The most connected area of high gray value was taken as the center to cut an image about 100×100 pixel area. Four characteristic parameters were extracted to distinguish the cracks on preserved eggshell, including the length of the crack, mean variance ratio, skewness and kurtosis. We put forward 4 characteristic parameters and use the cluster analysis to detect cracks. Info-Kmeans clustering algorithm was used in this study, and the clustering of high-dimensional sparse data were extracted from the images. The results showed that all preserved eggs were classified into intact and cracked groups, and the accuracy rate was 93%. In this experiment, the sensitivity and specificity were 100%and 88.3%, the detection rate of intact preserved egg was 100%. The validation experimental result showed that the accuracy was 94%, and the sensitivity and specificity were 100%and 88.3%. Results showed that the model could distinguished intact and cracked preserved eggs efficiently, and it was great potential to detect cracks on product lines.