激光与红外
激光與紅外
격광여홍외
LASER & INFRARED
2014年
1期
30-34
,共5页
C-V模型分割%数学形态学%红外图像处理%小波阈值降噪
C-V模型分割%數學形態學%紅外圖像處理%小波閾值降譟
C-V모형분할%수학형태학%홍외도상처리%소파역치강조
C-V model segmentation%mathematical morphology%infrared image processing%wavelet threshold de-noi-sing
为了从红外热图像中分割和识别出碳/碳构件的缺陷,提出了一种C-V模型分割和数学形态学处理相结合的红外图像处理新方法。该方法首先用小波阈值降噪法对采集的红外热图像进行去噪声处理,提高图像的信噪比。然后采用基于C-V模型分割法对红外图像进行分割,再用Canny算子提取出缺陷轮廓;最后运用数学形态学方法平滑缺陷轮廓,去除轮廓外的孤立像素点;最终求得缺陷的实际面积。实验结果表明,该方法能很好地分割出构件中的缺陷,计算误差在6%以内;能处理十分模糊的红外图像,缺陷轮廓的提取较为准确,定位精度高。
為瞭從紅外熱圖像中分割和識彆齣碳/碳構件的缺陷,提齣瞭一種C-V模型分割和數學形態學處理相結閤的紅外圖像處理新方法。該方法首先用小波閾值降譟法對採集的紅外熱圖像進行去譟聲處理,提高圖像的信譟比。然後採用基于C-V模型分割法對紅外圖像進行分割,再用Canny算子提取齣缺陷輪廓;最後運用數學形態學方法平滑缺陷輪廓,去除輪廓外的孤立像素點;最終求得缺陷的實際麵積。實驗結果錶明,該方法能很好地分割齣構件中的缺陷,計算誤差在6%以內;能處理十分模糊的紅外圖像,缺陷輪廓的提取較為準確,定位精度高。
위료종홍외열도상중분할화식별출탄/탄구건적결함,제출료일충C-V모형분할화수학형태학처리상결합적홍외도상처리신방법。해방법수선용소파역치강조법대채집적홍외열도상진행거조성처리,제고도상적신조비。연후채용기우C-V모형분할법대홍외도상진행분할,재용Canny산자제취출결함륜곽;최후운용수학형태학방법평활결함륜곽,거제륜곽외적고립상소점;최종구득결함적실제면적。실험결과표명,해방법능흔호지분할출구건중적결함,계산오차재6%이내;능처리십분모호적홍외도상,결함륜곽적제취교위준학,정위정도고。
In order to segment and recognize the defects in C/C component,an infrared image processing algorithm based on C-V model and mathematical morphology is presented.First,an original image was de-noised by wavelet threshold de-noising method to improve the SNR of the image.Then,the de-noised image was segmented based on C-V model.The contours of defects were also detected by canny operator.Finally,mathematical morphology methods were used to smooth the contours and to remove isolated pixels outside the contours.The areas of the defects were also cal-culated.The results show that the defects are well segmented with this algorithm and that the calculation errors are within 6%.The very vague infrared images can be well processed with this algorithm.The contours of defects are also well detected with high locating accuracy.