使用Zernike Moments之旋轉不變特徵來估計影像旋轉角

Abstract

本論文提出一種估計影像旋轉角的方法，此種方法假設影像的旋轉中心為已知，因此可以從旋轉影像與參考影像的比較中估計出準確的影像旋轉角。同時，我們改良Zernike moments的演算法，並利用重新取樣與內插演算法等技巧，能夠在不改變影像擷取硬體設備的前提下，提升影像解析度，也進一步地計算出更準確的Zernike moments值。另一方面，我們利用K-means分群法則，在所有Zernike moments所抽取出影像旋轉可能的角度中，準確地分類出有效的數值，再經由以重建為基礎的加權函數之運算，最後能獲得高準確度的影像旋轉角估計值。 在本篇論文中有兩個實驗，一個是以由模擬產生旋轉影像為對象的實驗，另一個是由以CCD攝影機所擷取的旋轉影像為對象的實驗。經由實驗結果顯示本論文所提出的新方法對於影像旋轉角的估計都有不錯的效果。

An estimation approach of image rotation angle is proposed here. A basic assumption that the center of image rotation must be known is made, so that we can estimate the precise image rotation angles from the comparison between the rotated images and the reference one. Furthermore, the Zernike moment algorithm with subsampling and interpolation techniques can increase the image resolution and compute Zernike moments more accurately on the premise that keep the image acquiring hardware instrument unchanged. In addition, a K-means clustering algorithm is used to classify valuable entries from all the rotation angle candidates extracted via Zernike moments and sum up them by weighting factors based on image reconstruction. After that, the estimation of image rotation angle with high resolution is derived. Two experiments are reported which are on rotated images generated by computer and captured by CCD camera, respectively. The experimental results show that the proposed method has good performance for image rotation angle estimation.