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研究生:劉祥暉
研究生(外文):Hsiang-Hui Liu
論文名稱:數位調諧器效能自動化測試
論文名稱(外文):Auto test of digital tuner performance
指導教授:劉如生
學位類別:碩士
校院名稱:元智大學
系所名稱:資訊工程學系
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:2009
畢業學年度:97
語文別:中文
論文頁數:51
中文關鍵詞:數位調諧器自動化測試HSI色彩空間干擾色塊網路攝影機
外文關鍵詞:Digital tunerauto testHSI color spacenoise blocksweb camera
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本論文所研製的數位調諧器自動化測試方法,主要利用網路攝影機取代傳統之人眼觀測法,具有客觀性,泛用性,及減少人力之優點,適用於各類數位調諧器無法利用位元錯誤率(bits error rate)測試時使用。
其中主要內容是利用網路攝影機取得待測的影像,經過空間轉換技術修正因網路攝影機擺放位置而產生之影像變形,接著利用HSI色彩空間分離出可疑的色塊干擾,最後利用Hough轉換篩選出確定的干擾色塊,以此測試數位調諧器是否已達到產品的解碼範圍。實驗結果將顯示所提方法的可行性。
The purpose of this thesis is to replace tradition test with eyes by auto test with web camera. In this thesis, many advantages are proposed for digital tuner auto test: objectiveness, generalization, and lower labor power. When digital tuner can not be test by BER (Bits Error Rate), the proposed method can be applied.
If the test image captured by web camera is deformed in shape, the proposed method will rectify the deformed image by spatial geometry transformation. After the rectifying process, each color pixel in the RGB color space is transformed to the HSI color space. The specific color blocks in HSI color space will be separated as candidate blocks. Finally, noise blocks will be screened out, and the respective maximum power and minimum power values of the digital tuner will be obtained. Experimental results proved the practicability of the proposed methods.
目錄
誌謝 I
中文摘要 II
英文摘要 III
目錄 IV
圖目錄 VI
表目錄 VII
第一章 序論 8
1.1 研究背景與動機 8
1.2 問題描述 3
1.3 相關研究 5
1.4 論文架構 7
第二章 系統架構與流程 8
2.1 系統設計概念 8
2.2 系統流程概觀 9
第三章 相關技術 11
3.1 RGB色彩空間特徵轉為HSI色彩空間特徵 11
3.2 HSI色彩空間特徵轉為RGB色彩空間特徵 15
3.3 直方圖投影 18
3.4 空間轉換 21
3.5 Hough轉換 24
第四章 實驗結果 26
4.1 實驗設備 26
4.2 實驗過程 28
4.3 實驗數據 38
4.4 實驗成效分析 45
第五章 結論及未來研究 48
5.1 結論 48
5.2 未來研究 49
參考文獻 50
參考文獻
[1] NorDig, NorDig Unified Test Specification, 2007. Available: http://www.nordig.org/
[2] K. Wogsritong, K. Kittayaruasiriwat, F. Cheevasuvit, K. Dejhan, and A. Somboonkaew, “Contrast enhancement using multipeak histogram equalization with brightness preserving,” IEEE Conference on Circuits and Systems, pp. 455-458, 1998.
[3] Y. Wang, Q. Chen and B. Zhang “Image enhancement based on equal area dualistic sub-image histogram equalization method,” IEEE Transaction on Consumer Electronics, Vol. 45, No. 1, pp. 68-75, 1999.
[4] Y. T. Kim, “Contrast enhancement using brightness preserving bi-histogram equalization,” IEEE Transaction on Consumer Electronics, Vol. 43, No. 1, pp. 1-8, 1997.
[5] S.Y. Kim, D. Han, S.J. Choi, and J.S. Rk, “Image contrast enhancement based on the piecewise-linear approximation of CDF,” IEEE Transaction on Consumer Electronics, Vol. 45, No. 3, pp. 828-834, 1999.
[6] A. F. Laine, S. Schuler, J. Fan, and W. Huda, “Mammographic feature enhancement by multiscale analysis,” IEEE Transaction on Medical Image, Vol. 57, No. 4, pp. 725-740, 1994.
[7] A. Laine and S. Song, “Multiscale wavelet representations for mammographic feature analysis,” Proc. SPIE Conference on Mathematical Methods in Medical Image, pp. 306-316, 1992.
[8] A. Laine and S. Song, “Wavelet processing techniques for digital mammography,” Proc. SPIE Conference on Visualization in Biomedical Computation, pp. 610-624, 1992.
[9] R. C. Gonzalez and R. E. Woods, Digital Image Processing, New York, Addison-Wesley, 2002.
[10] H. Ibrahim and N.S.P. Kong, “Brightness preserving dynamic histogram equalization for image contrast enhancement,” IEEE Transactions on Consumer Electronics, Vol. 53, No. 4, pp. 1752-1758, 2007.
[11] S.F. Sheu, A Study of Deblocking Filter for Video, Unpublished doctoral dissertation, National Cheng Kung University, Tainan, pp 9-11, 2002.
[12] ISO/IEC 13818-2 “Generic coding of moving pictures and associated audio,” part2: video, Nov. 1993.
[13] A.L. Kesidis, N. Papamarkos, “On the inverse Hough transform,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 21, No. 12, pp 1329-1343, 1999.
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