在影像追尋中光流法(Optical flow)是常使用的方法之一，其優點在於不需事先得知目標物的特徵，僅藉由亮度資訊之獲得，即可求得物體位移距離，因此適合應用於未知目標物的追尋。而昆蟲由於其獨特的複眼架構，在大自然界儼然成為追尋及捕捉獵物的佼佼者。如果能掌握昆蟲複眼的優勢所在，對於運動目標的追尋應可發揮莫大的提升作用。
然而，傳統的影像資訊乃建構於直角座標系上，與昆蟲複眼的六角架構截然不同。因此本論文目的在於，結合六角的概念與光流技術，探討與傳統直角系統的差異，以期對於昆蟲複眼在影像追尋優勢的背後原因有所初步了解，進而為爾後六角在影像實際應用之可行性奠定基礎。經過對於各種不同特徵影像電腦模擬結果顯示，六角格子之光流法整體而言追尋效果優於傳統直角格子之光流法。

The optical flow has been one of the common approaches for image tracking. Its advantage is that no prior knowledge for image features is required. Since movement information can be obtained based on brightness data only, this method is suitable for tracking tasks of unknown objects. Besides, insects are always masters in chasing and catching preys in the natural world due to their unique compound eye structure. If the edge of the compound eye can be applied to tracking of moving objects, it is highly expected that the tracking performance will be greatly improved.
Conventional images are built on a Cartesian reference system, which is quite different from the hexagonal framework for the compound eye of insects. This thesis explores the distinction of the hexagonal image framework by incorporating the hexagonal concept into the optical flow technology. Consequently, the reason behind why the compound eye is good at tracking moving objects can be revealed. According to simulation results for test images with different features, the hexagonal optical flow method appears to be superior to the traditional optical flow method in the Cartesian reference system.

目錄 I
圖索引 III
表索引 V
摘要 VI
Abstract VII
第一章 緒論 1
1.1 動機與目的 1
1.2 文獻回顧 1
1.3 論文架構 5
第二章 六角座標 6
2.1 對稱六角座標系 6
2.2 影像轉換 7
第三章 光流系統 13
3.1 光流及影像流之定義 13
3.2 以一階最小平方法求解光流法 14
3.3 以六角格子概念求解光流法 20
第四章 模擬 28
4.1 模擬流程 28
4.2 模擬結果 33
第五章 結論與未來展望 45
參考文獻 48
附錄A　六角光流之簡化解法 50
附錄B　微分區域選取 57
附錄C　模擬結果之數據 64

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