本實驗針對待修補物體的邊緣進行修補，在以前的研究中，對於物體邊緣的修補都是先手動將物體邊緣找出來，再利用提出的演算法去修補。本實驗所提出的是一種自動預測物體邊緣的方法，將有可能的物體邊緣預測出來，再利用我們提出的修補演算法，其對於物體邊緣之修補有不錯的結果。 本實驗主要是先對待修補圖片進行前處理，前處理包括，R.G.B轉H.S.I顏色空間模型，對比伸張(Contrast Strength)，Sobel邊緣偵測，Otsu 二值化，封閉運算(Closing)，細化(Thining)，將前處理過後的圖片去做毀損邊緣的預測，最後利用我們出的修補演算法去修補。 In this thesis, a new approach is presented for restoration of damaged portions of images. The algorithm first locates several feature points on the boundary of the damaged region of a given image. Missing curves are then automatically predicted and reconstructed by using the B-spline technique. Finally, a method that combines the advantages of texture synthesis and image inpainting is applied to restore the remaining damaged portion. Our experimental results are good for object’s edge. Our method focuses on only one-curve/edge prediction. However, there might be more than one missing curve/edge in a damage image. Recently, we are focusing on detection of more than one missing curve/edge in damage images and hoping to accomplish a more applicable and effective restoration scheme.
