模式识别与人工智能
模式識彆與人工智能
모식식별여인공지능
Moshi Shibie yu Rengong Zhineng
2013年
3期
276-281
,共6页
周韬%张茂军%熊志辉%徐玮
週韜%張茂軍%熊誌輝%徐瑋
주도%장무군%웅지휘%서위
仿射不变%图像特征%小波
倣射不變%圖像特徵%小波
방사불변%도상특정%소파
Affine Invariant%Image Feature%Wavelet
提出一种鲁棒的图像局部仿射不变特征提取方法.该方法首先对图像进行M进制小波变换,根据M进制小波变换系数的能量性质来检测图像特征点.然后以检测到的稳定特征点为中心,根据特征点周围的局部图像信息,以矩的形式构造仿射不变特征描述子.实验结果证明该方法对图像的旋转变化、尺度变化、视点变化、平移等所有仿射变换均具有较好的不变性.
提齣一種魯棒的圖像跼部倣射不變特徵提取方法.該方法首先對圖像進行M進製小波變換,根據M進製小波變換繫數的能量性質來檢測圖像特徵點.然後以檢測到的穩定特徵點為中心,根據特徵點週圍的跼部圖像信息,以矩的形式構造倣射不變特徵描述子.實驗結果證明該方法對圖像的鏇轉變化、呎度變化、視點變化、平移等所有倣射變換均具有較好的不變性.
제출일충로봉적도상국부방사불변특정제취방법.해방법수선대도상진행M진제소파변환,근거M진제소파변환계수적능량성질래검측도상특정점.연후이검측도적은정특정점위중심,근거특정점주위적국부도상신식,이구적형식구조방사불변특정묘술자.실험결과증명해방법대도상적선전변화、척도변화、시점변화、평이등소유방사변환균구유교호적불변성.
@@@@A robust affine invariant local image features extraction method is proposed. Firstly, the image is transformed with M band wavelet. The feature points of the image are detected according to the energy of the M band wavelet transform coefficients. Then, every detected feature point is set to be a center. According to the local image information around the center, affine invariant feature is constructed with a moment structure. The experiments prove the invariant efficiency of the proposed method in image rotation, shift, scaling and viewpoint change etc.