本論文提出一個簡單的旋轉不變特點應用於主動式雙眼視覺相機即時校正並硬體實現。我們所提出的不變特徵點結合了FAST 特徵點偵測與樣型基礎的BRIEF特徵點描述。相較於目前主流的SIFT特徵點，簡單的旋轉不變特徵點較簡單、快速且仍然可靠的，因此它更加符合雙眼視覺相機的即時校正。除此之外，由於特徵點的描述是二進制的代碼，更可以加速在特徵點的配對上。藉著左右眼影像上特徵點的關聯性，可以去計算出轉換矩陣並達成雙眼視覺相機校正之目的。
　　在硬體系統上，我們設計流水線的流程，可以讓硬體獲得充分的利用，也將特徵點偵測與特徵點的描述平行執行，加速其演算法。另外，將耗時的特徵點配對整合進硬體中，讓整個系統更加完整也更快速。從實驗中得知，每秒可以處理約100張畫面在47.9 MHz 的時脈下，它的校正表現和SIFT 是不相上下的。我們所提出的系統不僅簡單快速，它的校正表現也是相當可靠的。

This thesis proposes simpler rotation-invariant features to be implemented on hardware and to rectify the stereo camera with active head. The invariant features combined the detector of features from accelerated segment test (FAST) and the feature descriptor of pattern-based binary robust independent elementary features (BRIEF). Comparing with popular invariant features such as scale-invariant feature transform (SIFT), the simpler rotation-invariant features we proposed are computationally faster and still reliable. Therefore, it is more suitable for the application on stereo rectification. Besides, due to the feature descriptor of binary string, it could promote the efficiency on feature matching. By minimizing the cost function over the obtained sparse set of correspondences between left and right views, we could estimate the essential matrix and achieve the goal of stereo rectification.
In the system of hardware, we design a pipeline flow and make the usage of hardware more efficient. A parallel architecture speeds up the parts of detector and descriptor. The time-consuming feature matching is also integrated into the system. 　It makes the system more complete. From the experimental result, its frame rate is up to 100 frames per second with the clock rate of 47.9 MHz and performance is comparable to SIFT. In conclusion, the proposed system is not only faster and simpler, but also still reliable for the application.

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