计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2015年
3期
152-156
,共5页
配准%印鉴边缘%尺度不变特征变换(SIFT)%变换模型%真伪识别
配準%印鑒邊緣%呎度不變特徵變換(SIFT)%變換模型%真偽識彆
배준%인감변연%척도불변특정변환(SIFT)%변환모형%진위식별
registration%edge of seal imprint%Scale Invariant Feature Transform(SIFT)%homography%verification
为了准确配准印鉴图像，为高仿真印鉴的真伪识别做好准备，提出利用印鉴边缘图像SIFT（Scale Invariant Feature Transform）特征的相似性和空间关系相结合的配准方法。采用邻域搜索法提取待测印鉴与预留印鉴的二值边缘图像，在印鉴边缘图像中提取SIFT特征，并根据相似性匹配。利用印鉴边缘图像SIFT特征匹配点对的空间关系剔除错误匹配，提高配准效率。利用RANSAC方法估计两印鉴的变换模型。分别配准具有不同形状及印文内容的10组真印鉴图像和10组假印鉴图像。将所得结果与其他两种典型的配准方法作比较。以两印鉴配准后不重合边缘点之间的平均距离评价配准的准确性，以最大距离量化配准后出现的最大差异。实验结果表明，该方法可以准确配准待测印鉴与预留印鉴图像，对印鉴形状、笔画结构无任何限制，配准速度比直接利用印鉴二值图像SIFT特征的配准方法提高一倍。
為瞭準確配準印鑒圖像，為高倣真印鑒的真偽識彆做好準備，提齣利用印鑒邊緣圖像SIFT（Scale Invariant Feature Transform）特徵的相似性和空間關繫相結閤的配準方法。採用鄰域搜索法提取待測印鑒與預留印鑒的二值邊緣圖像，在印鑒邊緣圖像中提取SIFT特徵，併根據相似性匹配。利用印鑒邊緣圖像SIFT特徵匹配點對的空間關繫剔除錯誤匹配，提高配準效率。利用RANSAC方法估計兩印鑒的變換模型。分彆配準具有不同形狀及印文內容的10組真印鑒圖像和10組假印鑒圖像。將所得結果與其他兩種典型的配準方法作比較。以兩印鑒配準後不重閤邊緣點之間的平均距離評價配準的準確性，以最大距離量化配準後齣現的最大差異。實驗結果錶明，該方法可以準確配準待測印鑒與預留印鑒圖像，對印鑒形狀、筆畫結構無任何限製，配準速度比直接利用印鑒二值圖像SIFT特徵的配準方法提高一倍。
위료준학배준인감도상，위고방진인감적진위식별주호준비，제출이용인감변연도상SIFT（Scale Invariant Feature Transform）특정적상사성화공간관계상결합적배준방법。채용린역수색법제취대측인감여예류인감적이치변연도상，재인감변연도상중제취SIFT특정，병근거상사성필배。이용인감변연도상SIFT특정필배점대적공간관계척제착오필배，제고배준효솔。이용RANSAC방법고계량인감적변환모형。분별배준구유불동형상급인문내용적10조진인감도상화10조가인감도상。장소득결과여기타량충전형적배준방법작비교。이량인감배준후불중합변연점지간적평균거리평개배준적준학성，이최대거리양화배준후출현적최대차이。실험결과표명，해방법가이준학배준대측인감여예류인감도상，대인감형상、필화결구무임하한제，배준속도비직접이용인감이치도상SIFT특정적배준방법제고일배。
Accurate registration is the key premise of accurate verification. A SIFT(Scale Invariant Feature Transform) feature based registration algorithm is presented to prepare for the seal verification, especially for the verification of high quality counterfeit sample seals. The similarities and the spatial relationships between the matched SIFT features are com-bined for the seal image registration. SIFT features extracted from the edge images of the binary model seal and sample seal images are matched according to their similarities. False matches are eliminated according to their position relationship. The homography between the model seal and the sample seal is constructed by RANSAC. In experiments, 10 pairs of gen-uine seal imprints and 10 pairs of fake are tested by the presented registration method and other two classical methods. The average distance between non-overlapped edges is obtained to assess the accuracy of registration, and the maximum distance quantifies the biggest difference between two seal imprints. Experiment results show that the presented method can accomplish more accurate registration, and there is no limit to the seal shapes, stroke number and structures. The regis-tration speed is doubled, compared to the registration method of using the SIFT in binary seal imprints.
