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研究生:林家儒
研究生(外文):Chia-Ju Lin
論文名稱:運用顏色與SURF關鍵點特徵分類之快速多廣告看板計次系統
論文名稱(外文):A Fast Multi-Banner Counting System using Color and SURF Key-Point Features Classification
指導教授:張厥煒張厥煒引用關係
指導教授(外文):Chueh-Wei Chang
口試委員:奚正寧楊士萱
口試委員(外文):Cheng-Ning HsiShih-Hsuan Yang
口試日期:2012-07-19
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:資訊工程系研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:中文
論文頁數:71
中文關鍵詞:廣告看板SURF特徵描述物件識別特徵篩選
外文關鍵詞:BannerSURFFeature DescriptionObject RecognitionFeature Extraction
相關次數:
  • 被引用被引用:7
  • 點閱點閱:284
  • 評分評分:
  • 下載下載:38
  • 收藏至我的研究室書目清單書目收藏:0
西元2012年在洛杉磯道奇隊主場(Dodger Stadium)的本壘板後方,再次出現台灣觀光局的廣告看板。觀光局表示,今年觀光局以新台幣一千多萬元經費,與道奇球團簽約一年,以看板展示的方式在道奇主場宣傳台灣觀光。由於眾多廣告看板都經電視轉播給全世界觀眾觀看,故不管是公司產品經營或是觀光政策,都常藉由高收視率的轉播來吸引更多人的注目,打響知名度。
本論文以顏色與SURF為主要特徵,透過顏色的濾除再以SURF特徵做辨識,搭配特徵在空間上的資訊及分布,篩選出適當且具代表性的關鍵點。並對於篩選後的關鍵點建立新的索引結構,能有效率的支援多重高維度特徵之搜尋。針對視覺影像為基礎的競賽轉播之廣告看板辨識系統。處理後的特徵可以讓每張廣告圖片保有獨特性、互斥性及唯一性的關鍵點。搭配畫面差異的偵測,可以大幅降低運算時間,而辨識部分利用特徵描述子的拉氏信號、特徵向量的距離以及合成向量的主要方向比對關鍵點的相似度。根據實驗的結果,利用篩選後的特徵排序加以比對能有效加速搜尋亦可以大幅度的減少比對次數。也能達到高準確率的比對結果。


In 2012, behind the home base in Los Angeles’ Dodger Stadium, once again there will be the billboard of Taiwan’s Tourism Bureau.
The Tourism Bureau has indicated that this year they have prepared a budget of 10 million NT dollar and signed a one year contract with the Dodger Stadium to utilize their billboards to promote Taiwan Tourism.
As these advertising billboards are visible to a worldwide audience via television broadcast, regardless of the item being promoted, increased awareness will be achieved by taking advantage of high rating broadcasted locations.
The main focus of this paper is of color and SURF. The representative features are identified through filtering by color and recognition of SURF characteristics as well as the distribution of space and information. This helps creating a new index structure with the main features specified, and allowing efficient multiple high-dimensional feature search whilst targeting the basis of visual imagery advertising through sports game broadcasting’s billboard recognition system.
The processed features allow each advertising image to maintain its uniqueness and mutually exclusive characteristics. In collaboration of detecting the frame differences, calculating frequency can be markedly decreased. Identification is made by comparison of the similarity of the feature points using sign of the laplacian, distance of the characteristic vectors and the main direction of the synthetic vector.
According to the test results, search is accelerated by using the identified main features as it also decreased the number of comparisons required, which in effect achieves more accurate results.


摘 要 i
ABSTRACT ii
致 謝 iv
目 錄 v
表目錄 viii
圖目錄 ix
第一章 緒 論 1
1.1 研究動機 1
1.2 研究目的與範圍 2
1.3 論文架構 5
第二章 相關研究與文獻探討 6
2.1 圖形匹配與廣告辨識 6
2.2 擷取物件特徵 9
2.2.1 色 彩 9
2.2.2 邊 緣 10
2.3 局部影像特徵 10
2.4 尺度不變特徵 11
2.5 SIFT特徵 12
2.6 PCA-SIFT 特徵 13
2.7 SURF 特徵 14
第三章 系統架構 19
3.1 系統概述 19
3.2 系統架構流程 21
第四章 特徵學習 23
4.1 顏色特徵擷取 24
4.1.1 色彩空間轉換 24
4.1.2 色彩直方圖 25
4.2 SURF關鍵點特徵擷取 28
4.3 關鍵點匹配方法 30
4.3.1 拉氏信號(Sign of the Laplacian)的比對 30
4.3.2 特徵描述子間的距離 31
4.3.3 合成向量的主要方向 33
4.3.4 辨識結果 33
4.4 特徵篩選 33
4.4.1 廣告看板分群 34
4.4.2 關鍵點篩選 35
第五章 廣告看板偵測 40
5.1 反向投影(Back Projection) 41
5.2 形態學處理 41
5.2.1 二值化 42
5.2.2 侵蝕與膨脹 42
5.2.3 尋找輪廓 44
第六章 廣告看板辨識 46
6.1 影像正規化 46
6.2 特徵匹配方法 49
6.3 辨識結果 51
第七章 實驗結果 53
7.1 實驗與系統環境 53
7.2 系統介面與功能 53
7.3 實驗結果與討論 57
第八章 結論與未來展望 66
8.1 結論 66
8.2 未來展望 66
參考文獻 68


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