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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/38921
Title: | 適應性搜尋步數與變焦追蹤演算法應用於自動聚焦 Auto Focus Using Adaptive Step Size Search and Zoom Tracking Algorithm |
Authors: | Chia-Hao Chang 張家豪 |
Advisor: | 傅楸善 |
Keyword: | 自動聚焦,變焦追蹤,適應性搜尋, Auto focus,adaptive search,zoom tracking, |
Publication Year : | 2005 |
Degree: | 碩士 |
Abstract: | 我們在這篇論文中提出了適應性搜尋步數自動對焦演算法以及變焦追蹤演算法。
目前存在著許多自動對焦搜尋演算法,像是全域搜尋,二元搜尋,費柏納西搜尋以及其他相關的搜尋演算法。全域搜尋可以保證找到最大的峰值(peak),但是其缺點為搜尋時間過長。二元搜尋以及費柏納西搜尋的搜尋時間減短了,但是鏡頭必須來回移動,容易造成定位上的失誤。我們的適應性搜尋步數演算法只有一次反向移動,而且搜尋的時間可以減少很多。 變焦追蹤是在變焦的時候持續的改變焦距來保持聚焦。常見的變焦追蹤演算法都是使用查表法加上內插法。但是表的大小常常有其限制。我們的變焦追蹤演算法可以有效的減少表的大小並且仍能保持聚焦。 In this thesis, an adaptive step size auto focus search algorithm and a reduced zoom tracking algorithm are proposed. Many different auto focus search algorithms exist, such as global search, binary search, Fibonacci search, and so on. Global search can ensure the global peak is found correctly, but the search time is too long. The search time of binary or Fibonacci search is shortened, but the lens has to move back and forth frequently, which is prone to have step errors. Our adaptive step size search algorithm performs only one backward movement while the search time is greatly decreased. Zoom tracking is to adjust a camera’s focal length continuously, to keep the in-focus state of an image during zoom operation. A simple table-lookup with interpolation method is commonly used, but the size of the table is important. Our reduced zoom tracking algorithm reduces the table size while still achieving good image quality. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/38921 |
Fulltext Rights: | 有償授權 |
Appears in Collections: | 資訊工程學系 |
Files in This Item:
File | Size | Format | |
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ntu-94-1.pdf Restricted Access | 1.85 MB | Adobe PDF |
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