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研究生(外文):Chiu, Ming-Hui
論文名稱(外文):Frequent Itemset Mining for Suggestion of Photo Style Imitation
指導教授(外文):Huang, Fay
口試委員(外文):Lee, Yeuan-KuenSun, Shih-Wei
外文關鍵詞:Frequent Itemset MiningImage Edge DetectionSalient Region Detection
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Nowadays, we live in an era which digital cameras and smartphones are very popular devices. Sharing photos on social networks using these devices has become a joyful habit in many people's lives. However not everyone is familiar with photography composition rules. Currently, the smart handheld devices are not yet equipped with the function of automatic photo composition adjustment. The major goal of this thesis is to develop a photo style imitation system. The system is able to assist users in better photo taking through a pre-learning process on a high quality image database.
In the learning process, frequent itemset mining algorithm was utilized to obtain a set of most frequent combinations of image characteristics, namely the style of the pictures, from the high quality image database. The obtained combinations of image characteristics were then used as bases for assisting composition of photographic image. In this thesis, totally 15 image characteristics were taken into account. Image edge detection method was used to determine the complexity of an image. Salient region detection algorithm was used to understand the main structure of the picture. Hue distribution was used to analyze the contrast of a color image.
The experimental results show that the developed system is able to characterize different styles of photos. Moreover, it is able to provide users suggestions on how to improve photo composition according to the image characteristic differences between the user input photo and the pre-learnt knowledge. Users may adjust some particular image characteristics of their photos according to the provided suggestions to improve the overall photo composition. This system can analyze the input photo and offer suggestions within one second, and thus potentially an App can be developed to become a built-in function for all smartphone cameras.
摘要 I
Abstract II
誌謝 III
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 1
1.3 論文架構 2
第二章 文獻探討 3
2.1 邊緣線條分析 3
2.2 顯著性區域分析 5
2.3 HSV空間色相分析 10
2.4 頻繁項目探勘 17
第三章 研究方法 20
3.1 流程介紹 21
3.2 十五項圖片風格屬性 24
3.2.1 圖片屬性一: 線條面積 25
3.2.2 圖片屬性二: 線條所占格子 27
3.2.3 圖片屬性三: 最多線條之直格 29
3.2.4 圖片屬性四: 最多線條之橫格 30
3.2.5 圖片屬性五: 未佔線條之直格數 32
3.2.6 圖片屬性六: 未佔線條之橫格數 33
3.2.7 圖片屬性七: 顯著性區域面積 36
3.2.8 圖片屬性八: 顯著性區域所占格子 38
3.2.9 圖片屬性九: 顯著性面積最大之直格 40
3.2.10 圖片屬性十: 顯著性面積最大之橫格 41
3.2.11 圖片屬性十一: 未有顯著性區域之直格數 43
3.2.12 圖片屬性十二: 未有顯著性區域之橫格數 44
3.2.13 圖片屬性十三: 顯著性區域之線條量 46
3.2.14 圖片屬性十四: 色相第一高峰和第二高峰距離 48
3.2.15 圖片屬性十五: 第一高峰色相顏色之面積 50
3.3 探勘出長度六的頻繁項目列 52
3.4 輸入圖並給出建議 54
第四章 實驗結果 56
第五章 結論與未來展望 78
參考文獻 79
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