| dc.contributor.advisor | 吳柏林 | zh_TW |
| dc.contributor.advisor | Wu, Ber Lin | en_US |
| dc.contributor.author (Authors) | 黃瑞華 | zh_TW |
| dc.contributor.author (Authors) | Huang, Jui Hua | en_US |
| dc.creator (作者) | 黃瑞華 | zh_TW |
| dc.creator (作者) | Huang, Jui Hua | en_US |
| dc.date (日期) | 2007 | en_US |
| dc.date.accessioned | 17-Sep-2009 13:48:52 (UTC+8) | - |
| dc.date.available | 17-Sep-2009 13:48:52 (UTC+8) | - |
| dc.date.issued (上傳時間) | 17-Sep-2009 13:48:52 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0094972003 | en_US |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/32594 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 應用數學研究所 | zh_TW |
| dc.description (描述) | 94972003 | zh_TW |
| dc.description (描述) | 96 | zh_TW |
| dc.description.abstract (摘要) | 本論文應用攝影構圖法則，以模糊邏輯理論為基礎，判別影像的攝影構圖類型。構圖(Composition)乃是攝影這項平面藝術創作最重要的美學元素之一，其目的是利用空間中的物體配置，經由透視投影後，讓畫面的整體呈現平衡感；專業的、優秀的攝影作品，皆會符合攝影的基本構圖原理。因此許多的影像增強、影像合成的應用中，也應該配合相片原本的構圖設計，針對所欲表達的重點予與適當地調整，而非「盲目的」以一體適用的法則去處理每一張照片。論文中，我們針對影像所欲表達的重點區域，分析其結構特性，設計不同的特徵，並以模糊邏輯理論為基礎，應用Mamdani系統，結合隸屬函數與攝影構圖判別法則的交互作用，用以辨認所欲處理相片的構圖類別。依據辨認後的構圖類別，即可對該影像做適當地分割及調整，以使相片能有最佳的影像增強處理。實驗證明，本文所提出的方法能有效地辨認攝影構圖類別，針對不同攝影構圖所作的影像修正，才能更符合人眼的視覺喜好。 | zh_TW |
| dc.description.abstract (摘要) | This thesis addresses the problem of how to recognize the photographic composition from a given photo based on the theory of fuzzy logic. Composition is one of the important aesthetics for the plane figure photo art. To present the balance of its holistic picture, it takes the advantage of special object arrangement after acting perspective projection. A piece of professional and qualified photo work will realize these basic photo composition methods. For many applications about the digital photo, the operations, i.e., photo enhancement, segmentation, output, and synthesis, all need to match up the photographic composition to do accurate processing rather than “blind” processing that assumes each photo with the same “composition.” An automatic recognition method using image features from some specific regions is described. The method is employed in a Mamdani model and combines outputs of multiple fuzzy logic rules and feature extraction algorithms to obtain confidences that can identify the correct photographic composition. Experimental results show that the proposed method is robust and effective for photographic composition recognition. The feature with adjusting in different photo composing will be able to comfort our human sight. | en_US |
| dc.description.tableofcontents | Abstract (in Chinese)Abstract (in English)AcknowledgementsContentsList of TablesList of FiguresCHAPTER 1 INTRODUCTION1.1 Motivation of the research1.2 Survey of related researches1.3 Sketch of the research work1.4 Thesis organizationCHAPTER 2 PRINCIPAL TYPES OF PHOTOGRAPHIC COMPOSITIONS2.1 Sun-like Composition (SC)2.2 Golden-section-like Composition (GC)2.3 Diagonal-like Composition (DC)2.4 Frame-like Composition (FC)2.5 Symmetry-like Composition (SMC)2.6 Triangle-like Composition (TC)2.7 Vanishing-point-like Composition (VC)2.8 Horizontal/vertical-line-like Composition (HVC)CHAPTER 3 FEATURES ANALYSIS AND EXTRACTION 3.1 Feature Analysis3.2 Features extraction 3.2.1 Feature 1: Sharpness3.2.2 Feature 2: Brightness average3.2.3 Feature 3~6: Local linearity3.2.4 Feature 7: Symmetry3.2.5 Feature 8~10: Global major line directionCHAPTER 4 FUZZY LOGIC FUSION4.1 Basic concepts4.2 Input variables4.3 Membership functions4.4 Fuzzy logic rule-based fusionCHAPTER 5 EXPERIMENTAL RESULTS5.1 The typical experiment5.2 The test setsCHAPTER 6 SUMMARY AND FUTURE RESEARCH 6.1 Summary and conclusions6.2 Topics for future researchREFERENCES List of TablesTable 1. The requirements of features extraction of 25 selected ROI’s. Table 2. True average values of 6 estimated features in 25 ROIs.Table 3. Confidences of 6 features in Table 2.Table 4. The fuzzy “High(H)” memberships of confidences in Table 3.Table 5. The memberships of 8 photographic compositions about the Fig. 6.Table 6.1. Sample images with sun-like composition.Table 6.2. Sample images with golden-like composition.Table 6.3. Sample images with diagonal-like composition.Table 6.4. Sample images with frame-like composition.Table 6.5. Sample images with symmetry-like composition.Table 6.6. Sample images with triangle-like composition.Table 6.7. Sample images with vanishing-point-like composition.Table 6.8. Sample images with Horizontal/Vertical-line-like composition.Table 7. The correlations between different photographic compositions and the outputs of fuzzy logic rules. List of FiguresFig. 1. The sun-like photographic composition.Fig. 2. The golden-section-like photographic composition.Fig. 3. The diagonal-like photographic composition.Fig. 4. The frame-like photographic composition.Fig. 5. The symmetry-like photographic composition.Fig. 6. The triangle-like photographic composition.Fig. 7. The vanishing-point-like photographic composition.Fig. 8. The horizontal/vertical-like photographic composition.Fig. 9. The locations of 25 ROI’s.Fig.10. Flowchart of the proposed algorithm for identifying the photographic composition based on fuzzy logic.Fig. 11. Two membership functions for input variables.Fig.12. The identifying system output membership functions.Fig. 13 (a) Test image. (b) The 25 ROI images with size 17×17.Fig. 14. The sharpness of 25 ROIs from the Fig. 13(b).Fig. 15. The edge map of the tested image in Fig. 13(a).Fig. 16. The four features of linearity of the tested image. The abscissa of the plots denotes the number of the ROI. Fig.17. The symmetric feature of all ROI pairs. The color blocks denote the corresponded ROI pair is referenced in the recognition procedure.Fig. 18. The Hough space of the tested imageFig. 19. The histogram of the directions of straight lines in the te | zh_TW |
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| dc.language.iso | en_US | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0094972003 | en_US |
| dc.subject (關鍵詞) | 模糊邏輯 | zh_TW |
| dc.subject (關鍵詞) | 影像特徵 | zh_TW |
| dc.subject (關鍵詞) | 圖形辨識 | zh_TW |
| dc.subject (關鍵詞) | 攝影構圖 | zh_TW |
| dc.subject (關鍵詞) | Fuzzy logic | en_US |
| dc.subject (關鍵詞) | Image features | en_US |
| dc.subject (關鍵詞) | Pattern recognition | en_US |
| dc.subject (關鍵詞) | Photographic composition | en_US |
| dc.title (題名) | 應用模糊邏輯的攝影構圖辨認方法 | zh_TW |
| dc.title (題名) | A Fuzzy Logic Approach for Recognition of Photographic Compositions | en_US |
| dc.type (資料類型) | thesis | en |
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