臺灣博碩士論文加值系統

目前桌球評判方式主要是靠人眼來決定得分與否。但在擊球速度過快或裁判個人因素而會出現誤判等情形。因此，有必要建立一套完整且準確的桌球自動裁判系統。在以往的相關應用當中以網球的鷹眼系統最為著名，其方法為追蹤記錄球的路徑並顯示記錄的實際路徑的圖形圖像，也可以預測球未來的路徑。

本篇文章將此大致概念運用至桌球比賽中，利用頂帽濾波器（tophat）來銳化桌球之桌緣，並利用形態學以及連通區域標記將桌球桌切割出來。桌網切割的部分為形態學搭配線性回歸的方式得出其直線方程式。接著利用前景灰階值扣除背景灰階值來保留移動物件，搭配形態學以及區域性偵測來提高偵測桌球球心之準確率。最後再將所得之三樣特徵值（桌球桌區域、桌球落點質心、桌網直線方程式）輸入至本桌球規則系統中來有效判別得分與否。本篇文章採用 JVC-GZ-GX1攝錄影機拍攝，並與人眼判別進行下列之比對，桌面切割、偵測桌球質心、落點、評分等準確率，平均準確率分別為 0.9919、0.8488、0.8460、及 0.8322。實驗結果證明本篇文章提出的演算法對桌球偵測與桌球自動判分有一定之準確率。

The current referee methods of table tennis games rely on the human eye to determine the score. However, fast hitting and the referee’s personal factors may cause misjudgment. Therefore, it is necessary to establish a complete and accurate automated referee system of table tennis games. The most famous related application is Hawk-Eye, to visually track the trajectory of the ball and display a record of its statistically most likely path as a moving image.

This article generally applies this concept to a table tennis game. First, use tophat filter to sharpen the edge of the table tennis table. Then, we can apply Morphology and labeling to detect the table tennis table. The part of the table tennis net detection utilizes Morphology and Linear Regression to find the net’s linear equation. After that, we can deduct the background intensities from the foreground intensities to retain the moving objects. And with morphological and regional detection, we can improve the accuracy of table tennis ball center detection. Finally, import the above results which are the table tennis table, the table tennis net’s linear equation, and the table tennis ball center to the automated referee system of table tennis games in order to distinguish score or not. This article uses JVC-GZ-GX1 camcorder to shoot, and compare with the human eye by the following features, which are the accuracy of table detection, ball detection, placement detection, and score. The average accuracies are 0.9919, 0.8488, 0.8460, and 0.8322. Experimental results show that the algorithm proposed in this article has high accuracy.

摘要 ..........................i
Abstract ..........................ii
Table of Contents ..........................iii
List of Tables ..........................v
List of Figures ..........................vi
Chapter 1 Introduction ..........................1
1.1 Background ..........................1
1.2 Motivation and goal ..........................3
1.3 Environment Settings ..........................5
1.4 Organization ..........................6
Chapter 2 Related Works ..........................8
2.1Morphology ..........................8
2.1.1Erosion ..........................8
2.1.2Dilation ..........................10
2.1.3Opening and Closing ..........................11
2.2Area Filling Algorithm ..........................13
2.3Connected Component Labeling ..........................14
2.4Otsu’s Thresholding ..........................15
2.5Linear Regression ..........................17
Chapter 3 ATTMU System ..........................19
3.1 Table detection ..........................20
3.2 Net detection ..........................24
3.3 Ball detection ..........................25
3.3.1Part A-Candidate point detection ..........................26
3.3.2Part B-Local area detection ..........................30
3.3.3Placement detection ..........................33
3.4Regular system ..........................35
3.4.1Effective service judgment ..........................35
3.4.2Effective service return judgment ..........................38
3.4.3Reset serving point ..........................40
Chapter 4 Results and Discussion..........................41
4.1 Experimental evaluation methods ..........................41
4.2 The experiment results of Table Detection ..........................43
4.3 The experiment results of Net Detection ..........................44
4.4 The experiment results of Ball Detection ..........................45
4.5 The experiment result of Regular System ..........................55
4.6 The efficacy of ATTMU ..........................56
Chapter 5 Conclusions and Future Prospects ..........................57
5.1 Conclusions ..........................57
5.2 Future Prospects ..........................58
Reference ..........................59

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