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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/35717

Title: 即時影像辨識與夜間視覺技術於小型船舶自航器設計之應用
Application of Real-Time Image Recognition and Night Vision Techniques to a Small Boat Autopilot Design
Authors: 陳俊宏
Contributors: NTOU:Department of Communications Navigation and Control Engineering
國立臺灣海洋大學:通訊與導航工程學系
Keywords: 自航控制器;白平衡設定;HSV色彩轉換;夜間視覺導引
Autopilot;White balance;HSV color space;night vision-guided
Date: 2013
Issue Date: 2013-10-07T02:58:12Z
Abstract: 本文旨在探討於夜間能見度受限之環境下,利用影像處理技術改善夜間影像受光暈干擾,導致影像辨識在夜間導引船舶入港應用受限之現象。實驗採用視覺導引概念並結合航向自航器,導引小型船舶自動行駛於規劃之進港航道上。本文於影像處理方面分為色彩與形狀特徵之探討,藉此提升夜間影像特徵辨識度,由於形狀特徵在夜間低照度環境下容易隨著距離產生變形,故最終選擇以色彩特徵做為實驗辨識依據。於色彩辨識部分利用HSV色彩空間中的直方圖方法選擇H色調(Hue)、S飽和度(Saturation)、V色深度(Value)之閥值範圍,以區隔相似色彩特徵之差異,並提升目標物的辨識度。實驗流程係於船艏處架設一般式CCD攝影機,並設定適當之快門、曝光量、白平衡等參數,來擷取目標物之影像區域。透過影像處理程序進行HSV色彩轉換,並選取影像感興趣區域來解算正確之疊標影像資訊,最終進行視覺導引之應用。本文採用傳統式前、後疊標擺設導航計算法則並配合內模式與模糊船舶自航控制器,驗證夜間影像經由影像前置處理改善後仍可應用於夜間視覺導引。本研究改善先前夜間實驗之藍色、綠色光源光暈易與白色光源混淆之現象,並利用HSV直方圖來增強色彩辨識度而有效的降低動態干擾源之影響。由實驗結果顯示,影像經改善後,其光源雜訊干擾明顯受到抑制,因此可辨識較多的色彩特徵。本文所提之方法改善先前僅可使用單一色彩做為實驗辨識目標之限制,因此更適合於船舶夜間視覺導引之應用。
This work is concerned with usage of image processing technology to improve the night vision image target recognition performance while employing the visual guidance concept to guide a small boat towards a prescribed straight water channel in the night time. Both the shape feature and color recognition have been considered in the target recognition algorithm. However the low visibility in night time condition easily leads to deformation of the target shape, and only the color recognition method is adopted in the experiments. Specifically the histogram information of HSV(Hue, Saturation, and Value) color space are used to select the appropriate threshold range of HSV to achieve more reliable real-time color image recognition. In the proposed approach, two LED panel targets are arranged in cascade on the quayside to form a leading line. The targets are detected by a CCD camera mounted on the bow and aligned with the center line of the boat, and appropriate camera parameters (Shutter, Exposure and White balance) are set in advance. Use of the histogram information in the processing of the target guarantees more precise thresholds of HSV. The ROI (Region of Interest) scheme is also adopted during the image processing process to enhance identifiability of the leading mark. Calculation of the heading deviation and tracking deviation angles of the boat is carried out by analyzing the displacements of the target centers relative to the CCD center line and these information are fed into the autopilot. This work adopts more sophisticated image processing technique to improve the color recognition performance and outperforms the previous study in which only the red LED can be used in the night time. The experimental results reveal that not only red LED but also blue and green LED can be adopted to guide the small boat into the port in the night. The proposed approach reduces the light disturbance effectively, and the image improvement results in a more identifiable color characteristics that are more suitable for night vision-guided applications.
URI: http://ethesys.lib.ntou.edu.tw/cdrfb3/record/#G0010067034
http://ntour.ntou.edu.tw/handle/987654321/35717
Appears in Collections:[通訊與導航工程學系] 博碩士論文

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