標題: | 嵌入式環車監控系統 An embedded system for vehicle surrounding monitoring |
作者: | 涂淵耀 Yuan-Yao Tu 陳永昇 Chen, Yong-Sheng 資訊科學與工程研究所 |
關鍵字: | 汽車環場影像監控;汽車監控;魚眼相機;魚眼相機校正;鳥瞰式;嵌入式系統;vehicle surrounding monitoring;vehicle surveillance;fisheye camera;fisheye camera calibration;bird's-eye view;embedded system |
公開日期: | 2008 |
摘要: | 我的碩士論文的研究題目是視訊式的停車駕駛輔助系統,目的是希望透過整合多台攝影機畫面,產生汽車周圍360 度的景象供駕駛人參考。這個問題牽涉到魚眼相機的影像校正、反扭曲、影像接合、以及嵌入式系統的影像處理等多項議題。
裝置在汽車前後左右的四台魚眼攝影機,畫面透過四分割器整合輸入到嵌入式系統(ADI 的Blackfin561),經過校正後在PC 上先產生Mapping table,嵌入式系統利用此mapping table 產生圖二的結果,並及時的輸出在液晶螢幕給汽車駕駛人參考。
當障礙物出現在畫面接合處時,會因為攝影機視角的不同的關係產生鬼影或消失的狀況。針對這個問題,我也提出了解決的方法,並實作在嵌入式系統上。 What surrounds a vehicle effects vehicle maneuvering. Since there are a lot of blind spots around a vehicle, which lead to difficult maneuvering and endanger passengers and pedestrians. In this thesis, we develop a low cost but efficiency driving assistant system which provides the surrounding image of a vehicle in bird’s-eye view. By using a DSP chip and a fast-image-stitching algorithm as well as 4 fisheye cameras mounted around a vehicle, this system can instantly generate a vertical view of the vehicle from the top. This enables the driver to have a bird’s-eye view of their car and its surroundings without any blind spots. We also propose a novel idea to ensure the obstacle’s figure will show on the bird’s-eye view image. This vehicle surrounding monitoring system involves two major techniques, one is to find out the pixel mapping relationship between fisheye cameras and bird’s-eye view image, and the other is the real time image processing in embedded system. We propose some simple methods to find out the mapping relationship, including the fisheye image distortion model, fisheye image warping and rectifying. Then, we generate a lookup table for speeding up image processing in embedded system. On the other hand, we utilize the memory hierarchical structure and apply pipeline mechanism to enhance the throughput of embedded system. We also implement a dynamic boundary idea to let the system automatically switch image sources and reduce probability of missing obstacle’s figure in bird’s-eye view image. Finally, a bird’s-eye view image is generated. With this bird’s-eye view surrounding monitoring system, drivers can quickly understand the surrounding environment around the vehicle. Driving and parking become more easily and safely. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#GT079655539 http://hdl.handle.net/11536/43343 |
顯示於類別: | 畢業論文 |