基於無線射頻與電腦視覺技術的停車位導引系統

Parking Guidance System Based on Radio Frequency and Computer Vision

10.6402/TPJ.201003.0041

黃志泰(Gai-Tai Huang)

停車空位偵測 ； 停車位導引系統 ； 角點偵測 ； 影像識別 ； 無線射頻 ； Parking spaces detection ； Parking guidance system ； Corner detection ； Vision-based system ； Radio Frequency ； ZigBee

運輸計劃季刊

39卷1期（2010 / 03 / 30）

41 - 72

繁體中文

在大型公共停車場中要尋找一個空的停車位，對駕駛來講是一大問題，目前臺灣已建置有各種不同的停車導引（管理）系統，不過直到現在大多無法真正做到引導駕駛到空停車位來停車。因此本文提出一套創新的基於無線射頻和電腦視覺技術的停車空位導引系統，我們結合無線導引感測網路與攝影監視系統，建構出一套容易安裝使用的停車位導引系統，並且開發出結合ZigBee與LED的動態導引資訊看板，以ZigBee作為控制訊號傳輸網路，在停車場中佈建出一個無縫隙的無線導引感測網絡。除此之外，我們提出一個以影像識別為基礎的非學習式停車空位偵測方法，這個方法只要簡單四大步驟，就能完成停車空位偵測。經由實驗驗證，這套系統在模擬或實際停車場環境中運作，皆獲得不錯的效果，因此，此一系統架構不失為改良現有系統的一個參考做法。

A major problem regarding large scale parking lots is having to search for a parking space. Parking space detection is one of the key technologies in parking guidance or management systems. In Taiwan various parking guidance or management systems have been proposed, but until recently all of them provided surplus information of parking spaces to the users only, and could not direct drivers to available spaces close to them. In this paper a novel parking guidance system based on radio frequency and computer vision is presented. The goal of this paper is to present a wireless guidance sensor network that combines with a visual-based surveillance system that can allow easy, inexpensive monitoring of the vehicle berth in a car park. The wireless guidance sensor nodes are small in size, low cost, easily installed, and use ZigBee wireless communication technology to direct drivers to available spaces close to them. In addition, we present an unsupervised vision-based system for parking lot occupancy detection. The proposed method exhibits low computation complexity and uses just a few processes. The method is based on four main processing stages. In the first section, a raw image acquired from a camera system is preprocessed to mark the regions of the parking spaces. In the second step, the raw image is converted to a gray image. In the following step, car characteristics in the gray image are detected via the Harris corner detection algorithm. Finally, a parking place status is evaluated. Experimental results from both artificial and real scenes show promising results even in quite challenging conditions. Nonetheless a scope for improvement of the presented method is given.

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