SIFT,SURF,ORB,FAST 特徵提取演算法比較

影象處理的基礎就是要進行特徵點的提取，feature(interest points) detect 的方法也在不斷的進步，邊檢測，角點檢測，直線檢測，圓檢測，SIFT特徵點檢測，同時描述符也在發展，為了匹配的高效，逐漸從高維特徵向量到二進位制向量…下面做一個簡單的羅列，並呼叫opencv API看看效果！
承接上一篇文章。

Feature Detection Methods List:

• Canny Edge Detect, A Computational Approach to Edge Detection, 1986. The Canny edge detector is an edge detection operator that uses a multi-stage algorithm to detect a wide range of edges in images.
• Harris, A combined corner and edge detector, 1988. considering the differential of the corner score with respect to direction directly.
• GFTT，Good Features to Track,1994, Determines strong corners on an image.
• Matas-2000, Robust Detection of Lines Using the Progressive Probabilistic Hough Transform. 霍夫變換檢測直線.
• SIFT,Distinctive Image Features from Scale-Invariant Keypoints,2004, invariant to image translation, scaling, and rotation, partially invariant to illumination changes and robust to local geometric distortion. 128-dim(512B).
• ORB, ORB: an efficient alternative to SIFT or SURF,2011，基於FAST和BRIEF，比SIFT快兩個數量級，可作為SIFT的替代(a fusion of FAST keypoint detector and BRIEF descriptor
  ). 32B binary descriptor.
• STAR，Censure: Center surround extremas for realtime feature detection and matching,2008,引用次數不高.scale-invariant center-surround detector (CENSURE) that claims to outperform other detectors and is capable of real-time implementation.

特徵點提取演算法比較(image dataset(27 pictures)):

上面是通過一些圖片集測的單單是feature detect 的時間，接下來通過一對圖片看看feature detect和compute feature descriptor總共花費的時間開銷（秒）：

可以看到計算descriptor的開銷還是很大的，這裡僅僅兩張圖片，所以主要開始是計算描述符，提取是很快的。

下面通過通過兩張圖片來看這幾個演算法匹配的效果，1639-1311-697表示圖片1，2分別提取了1639，1311個keypoints，其中匹配的有697個。

Canny Edge Detection效果：

Find line segments by probabilistic Hough transform：

Harris Corner Detection：

SIFT match效果圖：

SURF match效果圖：

ORB match效果圖：

BRISK match效果圖：

程式碼在這裡