臺灣博碩士論文加值系統

隨著資訊科技日益發展，網路逐漸成為現代人主要交流的方式之一，網路拍賣市場也蓬勃發展，其中服飾是人們最常購買的品項，相信大家都有過經驗，衣服穿在模特兒身上是好看的，但收到實品時卻發現不適合自己，因此，若是有虛擬試衣系統，就能在線上搭配，待確認是否合適再購買，如此一來可以節省使用者許多時間和金錢，一舉數得。
　　本篇研究藉由CMOS相機拍攝人像及上衣影像，經由影像前處理，將彩色影像分別分離成R、G、B三個平面及灰階化處理，共四張影像，接著使用Sobel濾波器分別偵測人像與服飾之影像邊緣，並透過閉合填補邊緣影像缺口及填滿邊緣影像，以達到擷取完整人像與上衣之目的，再來利用完整的人像做直方圖分析，將人像的肩線以及中線劃分出來，至於服飾則使用偵測領口最高點來加以定位。最後檢測人像之肩膀寬度及上半身長度，並且縮放上衣大小後，即可根據定位點將上衣套於使用者身上。
實驗結果顯示，使用本方法可以準確的定位出肩線及中線，以利於上衣套用於使用者，達到試衣之功效。

　With the increasing development of information technology, internet has become one of the modern major means of communication. The Internet auction market is also booming, where costumes are the most frequently purchased items. However, people have experienced that clothes on mannequin is nice, but the actual product received is found not suitable for them. Therefore, if there is virtual fitting system, you can match online to confirm whether it is right to buy so to save users a lot of time and money and so on.
　　This study takes portrait and jacket images by a CCD camera. By pro-processing images, color images are separated into R, G, B three planes and grayscale processing, a total of four images. Then it is followed by using the Sobel filter to detect the measured edge of portraits and costumes images.
　　It is also through closing the edge image gaps and filling the edge image to achieve completing capture of portraits and clothes. Using the full portrait histogram analysis again will partition the shoulder line and midline of the portrait. As for the costumes the highest point of neckline is used for positioning. At last through the inspection of portrait shoulder width and upper body length, and scaling shirt size, the jacket can be set on users based on located points.
Experimental results show that using this method can accurately locate the shoulder line and the midline of a jacket, so it is applied to facilitate the user to achieve the effect of fitting.

中文摘要 I
Abstract III
致謝 V
目錄 VI
表目錄 VIII
圖目錄 IX
第1章 緒論 1
1.1 研究背景 1
1.2 研究動機與目的 2
1.3 文獻探討 3
1.4 章節概要 5
第2章 相關原理 6
2.1 色彩空間轉換(Color Transfer) 6
2.1.1 RGB色彩空間 6
2.1.2 YIQ色彩空間 10
2.1.3 HSV色彩空間 11
2.2 二值化(Binarization) 13
2.3 影像分割(Segmentation) 16
2.4 形態學(Morphology) 17
2.4.1 膨脹(Dilation) 18
2.4.2 侵蝕(Erosion) 19
2.4.3 斷開(Opening) 20
2.4.4 閉合(Closing) 21
2.5 直方圖(Histogram) 22
2.6 試衣鏡原理(Principle of Virtual Mirrors) 23
第3章 演算法 24
3.1 影像前處理 26
3.2 邊緣偵測 28
3.3 影像填補 30
3.4 直方圖分析 32
3.5 衣服試穿 33
第4章 實驗結果 34
4.1 實驗環境 34
4.1.1實驗結果概述 35
4.2 衣服提取之實驗結果 37
4.3 人像提取之實驗結果 59
4.4 衣服試穿之實驗結果 67
4.5 與其他方法比較 72
第5章 結論與未來方向 76
5.1 結論 76
5.2 未來方向 76

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