可參數化控制K色以節省CMY色之演算法｜國立臺灣科技大學博碩士論文系統

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研究生：	曾盛嵩 Sheng sung Tseng
論文名稱：	可參數化控制K色以節省CMY色之演算法 A Parameterized-K Algorithm to Save CMY Color Toner Usage
指導教授：	許孟超 Mon-Chau SHIE
口試委員:	林昌鴻　 C. H. Lin 阮聖彰 Shanq-Jang Ruan
學位類別：	碩士 Master
系所名稱：	電資學院 - 電子工程系 Department of Electronic and Computer Engineering
論文出版年：	2010
畢業學年度：	98
語文別：	中文
論文頁數：	114
中文關鍵詞：	CMYK色
外文關鍵詞：	CMYK tones
相關次數：	點閱：112 下載：1
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本論文在闡述新發明彩色圖文之近似K分離之有效演算法，彩色圖文的K色通常用黑色碳粉會較便宜，雖然C，M，Y也可以組合成黑色，但是彩色碳粉通常較昂貴，處理近似黑色部份時避免用C，M，Y三色去混合而造成浪費。
本論文的特點在把落在近似黑白區的彩色像素用灰階圖取代，使人眼無法察覺其變化，除了維持圖形原本的視覺效果之外，也達到節省彩色碳粉的使用量，實驗結果證實其節省比率可達到驚人的效果，例如：在本實驗設參數I為15的測試結果比例達49.7%之數據，表示平均近一半的彩色像素可以用此演算法來處理，省下的數量用黑色碳粉取代列印，如此不僅可省下大量的彩色碳粉，品質方面也感受不到有任何的影響。
對公式{ abs[abs(R) - abs(G)] <= I } and { abs[abs(G) - abs(B)] <= I }
and { abs[abs(B) - abs(R)] <= I }作運算
而近似K的範圍可用一個參數值I來控制，故稱為可參數控制的近似K像素，I的參數值越高，省下的比例越高，但是須控制其失真度不讓品質受影響。
現今節能省碳已成主流，這個技術若能大量用在廣告印刷業，必能節省大量成本。

In this paper, a new invention in the color printer of a valid approximate K separation algorithm, color printer of the K toner black color normally will be cheaper. Although the C, M and Y toners also can be mixed for black color, but the part of black color solved by mixing C, M and Y toners is more expensive.
In this paper, the characteristics of black and white area in the fall similar to the color pixel map using grayscale replaced makes eye can not detect its changes, in addition to maintaining the original graphic visual effects, but also to achieve savings in color toner usage, experimental results confirmed that the savings rate can achieve amazing results, for example: in this experiment I set up parameters of the test results of 15 the proportion of up to 49.7% of the data, indicating an average of nearly half of the color pixel can use this algorithm to deal with, the amount saved by Black Toner to replace the print, so not only can save a lot of color toner, the quality also do not feel any impact.
By formula :
{ abs[abs(R) - abs(G)] <= I } and { abs[abs(G) - abs(B)] <= I }
and { abs[abs(B) - abs(R)] <= I } for computing .
The approximate range of K, a parameter value “I” can to control, so as to
approximate K pixel parameter control, “I” parameter values higher, the higher the proportion of savings, but it must not let the quality control of its distortion affected.
Today's energy-saving carbon has become the mainstream the technology used in the ad if a large number of the printing industry, will be able to save a lot of cost.

論文摘要	I
Abstracts	II
目錄	V
圖索引	VI
表索引	X
第1章  緒論	1
1-1 研究背景	1
1-2 研究之動機	1
1-3 研究之目的	2
第2章  基本觀念	3
2-1 簡介	3
2-2 技術說明	3
2-3 演算法	4
2-4 Matlab 影像處理基本指令	7
2-4-1 讀取影像檔案資料(imread())	8
2-4-2 將影像資料寫入檔案(imwrite())	9
2-4-3 將影像資料顯示在螢幕(imshow())	9
2-5單像素運算	9
    2-5-1 對於落在近似K的像素[100 100 100]，I=15時	9
2-5-2 對於落在非近似K的像素[50 100 50]，I=15時	12
2-5-3 PSNR 驗證	14
第3章  可參數化控制K色之實作流	16
   3-1 程式設計流程………………………………………………………………………… 16
3-2固定I值的實例操作及輸入輸出分析…………………………………………………20
3-2-1實例一(flowers.bmp)……………………………………………………………….20
3-2-2實例二(airplane.bmp)………………………………………………………………24
3-2-3實例三( soccer.bmp)…………………………………………………………………31
    3-3 PSNR測試值………………………………………………………………………………36
    3-4 印出後再掃描之PSNR比對……………………………………………………………36
3-4-1 flowers.bmp 各I值的印出掃描圖…………………………………………………37
    3-4-2 airplane.bmp 各I值的印出掃描圖………………………………………………..37
3-4-3 soccer.bmp 各I值的印出掃描圖……………………………………………………38
第4章 實作流程驗證與測試結果	39
4-1軟硬體平台介紹	40
4-2不同圖型的輸出	41
4-3測試結論	94
第5章 總 結	98
5-1 結論	98
5-2 應用及未來	100
參考文獻	103
附錄A	105

                                

[1] Alasdair McAndrew, Introduction to Digital Image Processing with Matlab, Thomson course Technology.
[2] Rafael C.Gonzalez,Richard E. Woods,Steven L. Eddins, Digital Image Processing using Matlab, Pearson Prentise Hall.
[3] 李宜達，第一章~第三章，動態模擬與繪圖/使用MATLAB/SIMULINK，全華科技圖書股份有限公司
[4] 張錚，第三章，第四章，第八章，Matlab教學範本程式設計與應用，知城數位
[5] 蒙以正，第二章，專業設計技巧MATLAB5，碁峯資訊
[6] Website, http://www.hlevkin.com/TestImages/classic.htm
[7] Website, http://www.hlevkin.com/TestImages/additional.htm
[8] Website http://www.mathworks.com/
[9] Zhaoyang, "Detection of Text Regions From Digital Engineering Drawings",IEEE Transactions on pattern analysis and machine intelligence, Vol. 20, No. 4, APRIL 1998,pp. 431~438
[10] Raashid Malik, SeongAh CHIN, "Extraction of Text in images",IEEE CNF
,Information Intelligence and Systems, 1999. Proceedings. 1999 International Conference on
31 Oct.-3 Nov. 1999 Page(s):534 - 537
Digital Object Identifier 10.1109/ICIIS.1999.810343
[11] P. Clark and M. Mirmehdi, "Combining Statistical Measures to Find Image Text Region",IEEE CNF , Pattern Recognition, 2000. Proceedings. 15th International Conference on
Volume 1, 3-7 Sept. 2000 Page(s):450 - 453 vol.1
Digital Object Identifier 10.1109/ICPR.2000.905373
[12] Q. Yuan, C. L. Tan, "Text Extraction from Gray Scale Document Images Using Edge Information",IEEE CNF,Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on
10-13 Sept. 2001 Page(s):302 - 306
Digital Object Identifier 10.1109/ICDAR.2001.953803
[13] Keechul Jung, Kwang In Kim, JungHyun Han, "Text Extraction in Real scene Images on Planar Planes", IEEE CNF, Pattern Recognition, 2002. Proceedings. 16th International Conference on
Volume 3, 11-15 Aug. 2002 Page(s):469 - 472 vol.3
Digital Object Identifier 10.1109/ICPR.2002.1047978
[14] Yefeng Zheng, Huiping Li, David Doermann, "Text Identification in noisy Document Images Using Markov Random Field", Document Analysis and Recognition, 2003. Proceedings. Seventh International Conference on
3-6 Aug. 2003 Page(s):599 - 603 vol.1

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