装甲兵工程学院学报
裝甲兵工程學院學報
장갑병공정학원학보
JOURNAL OF ARMORED FORCE ENGINEERING INSTITUTE
2012年
3期
61-64
,共4页
黄应清%赵锴%蒋晓瑜%田宏亮%魏磊
黃應清%趙鍇%蔣曉瑜%田宏亮%魏磊
황응청%조개%장효유%전굉량%위뢰
小波矩%Hu矩%支持向量机%识别
小波矩%Hu矩%支持嚮量機%識彆
소파구%Hu구%지지향량궤%식별
wavelet moment%Hu moment%Support Vector Machine (SVM)%recognition
分析了应用小波矩特征进行地面复杂背景下装甲车辆识别的理论依据,实地采集了某型坦克和某型步兵战车的灰度图像,提取其小波矩特征,采用支持向量机进行分类识别,进行了性能测试实验。结果表明:归一化后的图像的小波矩特征具有良好的不变性;小波矩特征对噪声和局部遮挡有较强的适应性,识别率比较稳定;支持向量机方法具有良好的分类识别能力。
分析瞭應用小波矩特徵進行地麵複雜揹景下裝甲車輛識彆的理論依據,實地採集瞭某型坦剋和某型步兵戰車的灰度圖像,提取其小波矩特徵,採用支持嚮量機進行分類識彆,進行瞭性能測試實驗。結果錶明:歸一化後的圖像的小波矩特徵具有良好的不變性;小波矩特徵對譟聲和跼部遮擋有較彊的適應性,識彆率比較穩定;支持嚮量機方法具有良好的分類識彆能力。
분석료응용소파구특정진행지면복잡배경하장갑차량식별적이론의거,실지채집료모형탄극화모형보병전차적회도도상,제취기소파구특정,채용지지향량궤진행분류식별,진행료성능측시실험。결과표명:귀일화후적도상적소파구특정구유량호적불변성;소파구특정대조성화국부차당유교강적괄응성,식별솔비교은정;지지향량궤방법구유량호적분류식별능력。
The theory that the wavelet moment could be applied to solve the problem of recognizing ar- mored vehicles under complex ground background is analyzed. True gray images of certain tank and infantry fighting vehicle are acquired, the features of wavelet moment are extracted, and classification and recognition are carried out by using Support Vector Machine (SVM). Performance test experiments are made, the results show that: the features of wavelet moments of the normalization images are stable; the characteristics of wavelet moment have better adaptation to noise and partial-cover, and the recognition rate is more stable ; the method of SVM has better capabilities of classification and recognition.