Improved Roberts focusing evaluation method for an autofocusing system

• Autorzy: Yin A. , Dai Z. , Chen B. , Li K.
• Języki publikacji: EN

Abstrakty

EN

In this paper, a new focusing evaluation method based on local 2/8 center windows is proposed for an autofocusing system. We have proposed an evaluation function which improved the Roberts function with eight-neighborhood or four-neighborhood. The approximate optimal criteria window is selected by a 2/8 rule. Comparative experiments implemented with other methods have shown that the 2/8 rule method not only can find the approximate optimal evaluation window quickly, but also has better generality. This evaluation function of improved Roberts’ function has higher sensitivity and better real-time performance.

Słowa kluczowe

EN

focus evaluation function; evaluation window; autofocusing

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Optica Applicata
• Rocznik: 2013
• Tom: Vol. 43, nr 3
• Strony: 529--538
• Opis fizyczny: Bibliogr. 27 poz., rys., tab., wykr.

Twórcy

autor

Yin A.

• The State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, China

autor

Dai Z.

• The State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, China

autor

Chen B.

• XJ Jingrui Science and Technology Co., Ltd, Xuchang, Henan, 461000, China

autor

Li K.

• School of Electrical, Electronic and Computer Engineering, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK

Bibliografia

• [1] GROEN F.C.A., YOUNG I.T., LIGTHART G., A comparison of different focus functions for use in autofocus algorithms, Cytometry 6(2), 1985, pp. 81–91.
• [2] BRAVO-ZANOGUERA M.E., LARIS C.A., NGUYEN L.K., OLIVA M., PRICE J.H., Dynamic autofocus for continuous scanning time-delay-and-integration image acquisition in automated microscopy, Journal of Biomedical Optics 12(3), 2007, article 034011.
• [3] YOUSEFI S., RAHMAN M., KEHTARNAVAZ N., GAMADIA M., A new auto-focus sharpness function for digital and smart-phone cameras, IEEE International Conference on Consumer Electronics (ICCE), 2011, pp. 475–476.
• [4] GAO X.G., SU W.M., GU H., A novel autofocus optimization algorithm based on minimum entropy criterion, Binggong Xuebao/Acta Armamentarii 31(12), 2010, pp. 1659–1662.
• [5] CHWAN-HSEN CHEN, TENG-LANG FENG, Fast 3D shape recovery of a rough mechanical component from real time passive autofocus system, The International Journal of Advanced Manufacturing Technology 34(9–10), 2007, pp. 944–957.
• [6] SHIH L., Autofocus survey: a comparison of algorithms, Proceedings of SPIE 6502, 2007, article 65020B.
• [7] DAIGO HOSHINO, TAKASHI YAMAUCHI, AKIRA WATANABE, TOSHIO ONODERA, HIDEHIRO HIGASHINO, Detection of actual focus variations by focus automatic measurement, Proceedings of SPIE 5040, 2003, pp. 861–870.
• [8] GYUNG BUM KIM, GUI YUN TIAN, A novel depth-from-focus-based measurement system for the reconstruction of surface morphology with depth discontinuity, The International Journal of Advanced Manufacturing Technology 40(11–12), 2009, pp. 1158–1165.
• [9] YU SUN, DUTHALER S., NELSON B.J., Autofocusing in computer microscopy: selecting the optimal focus algorithm, Microscopy Research and Technique 65(3), 2004, pp. 139–149.
• [10] SANG-YONG LEE, KUMAR Y., JI-MAN CHO, SANG-WON LEE, SOO-WON KIM, Enhanced autofocus algorithm using robust focus measure and fuzzy reasoning, IEEE Transactions on Circuits and Systems for Video Technology 18(9), 2008, pp. 1237–1246.
• [11] QUANDAI WANG, YUGANG DUAN, BINGHENG LU, JIAWEI XIANG, LIANFA YANG, Implementation of autofocus in alignment system for layered imprint fabrication, Transactions of Tianjin University 15(4), 2009, pp. 294–299.
• [12] KAUTSKY J., FLUSSER J., ZITOVÁ B., ŠIMBEROVÁ S., A new wavelet-based measure of image focus, Pattern Recognition Letters 23(14), 2002, pp. 1785–1794.
• [13] GUANG-HUA ZONG, MING-LEI SUN, SHU-SHENG BI, DAI DONG, Research on wavelet based autofocus evaluation in micro-vision, Chinese Journal of Aeronautics 19(3), 2006, pp. 239–246.
• [14] ZHIGANG FAN, SHOUQIAN CHEN, HAILI HU, HONG CHANG, QIANG FU, Autofocus algorithm based on wavelet packet transform for infrared microscopy, [In] 2010 3rd International Congress on Image and Signal Processing (CISP), Vol. 5, 2010, pp. 2510–2514.
• [15] ZHENG-YONG WANG, XIAO-HAI HE, XIAO-HONG WU, An autofocusing technology for core image system based on lifting wavelet transform, Journal of Sichuan University (Natural Science Edition) 45(4), 2008, pp. 838–841.
• [16] MAHMOOD M.T., TAE-SUN CHOI, SEONG-O SHIM, Shape from focus using principal component analysis in discrete wavelet transform, Optical Engineering 48(5), 2009, article 057203.
• [17] AIJUN YIN, BENQIAN CHEN, YI ZHANG, Focusing evaluation method based on wavelet transform and adaptive genetic algorithm, Optical Engineering 51(2), 2012, article 023201.
• [18] MALIK A.S., TAE-SUN CHOI, Consideration of illumination effects and optimization of window size for accurate calculation of depth map for 3D shape recovery, Pattern Recognition 40(1), 2007, pp. 154–170.
• [19] JAEHWAN JEON, INHYE YOON, DONGGYUN KIM, JINHEE LEE, JOONKI PAIK, Fully digital auto-focusing system with automatic focusing region selection and point spread function estimation, IEEE Transactions on Consumer Electronics 56(3), 2010, pp. 1204–1210.
• [20] KANG-SUN CHOI, JUN-SUK LEE, SUNG-JAE KO, New autofocusing technique using the frequency selective weighted median filter for video cameras, IEEE Transactions on Consumer Electronics 45(3), 1999, pp. 820–827.
• [21] LIAN-JIE LIU, YA-YU ZHENG, JIA-QIN FENG, LI YU, A fast auto-focusing technique for multi-objective situation, [In] 2010 International Conference on Computer Application and System Modeling (ICCASM), Vol. 1, 2010, pp. 607–610.
• [22] GUI YUN TIAN, GLEDHILL D., TAYLOR D., Comprehensive interest points based imaging mosaic, Pattern Recognition Letters 24(9–10), 2003, pp. 1171–1179.
• [23] ETZ S.P., JIEBO LUO, Ground truth for training and evaluation of automatic main subject detection, Proceedings of SPIE 3959, 2000, pp. 434–442.
• [24] CHENGXIN YAN, NONG SANG, TIANXU ZHANG, Local entropy-based transition region extraction and thresholding, Pattern Recognition Letters 24(16), 2003, pp. 2935–2941.
• [25] BING XIA, HENG PAN, QIUSHENG ZHENG, FENGJUN MIAO, Application of D-S evidence theory to uncertainty of assessment result in e-government, 7th Web Information Systems and Applications Conference (WISA), 2010, pp. 225–228.
• [26] TIAN G.Y., WILSON J., CHENG L., ALMOND D.P., KOSTSON E., WEEKES B., Pulsed eddy current thermography and applications, New Developments in Sensing Technology for Structural Health Monitoring, Lecture Notes in Electrical Engineering, Vol. 96, 2011, pp. 205–231.
• [27] FAN K.-C., LEE M.-Z., MOU J.-I., On-line non-contact system for grinding wheel wear measurement, The International Journal of Advanced Manufacturing Technology 19(1), 2002, pp. 14–22.