Cong-peng ZHANG, Wen-zheng CAO, Ming-gang XU, et al. Automatic focusing of micro-vision detection system of Mycobacterium tuberculosis smear[J]. Optics and precision engineering, 2018, 26(6): 1480-1488.
DOI:
Cong-peng ZHANG, Wen-zheng CAO, Ming-gang XU, et al. Automatic focusing of micro-vision detection system of Mycobacterium tuberculosis smear[J]. Optics and precision engineering, 2018, 26(6): 1480-1488. DOI: 10.3788/OPE.20182606.1480.
Automatic focusing of micro-vision detection system of Mycobacterium tuberculosis smear
Most of the medical smears of Mycobacterium tuberculosis have the characteristics of sparse and uneven content and more impurities in the observation area. There are some problems while observing the Mycobacterium tuberculosis smears to acquire image automatically
such as difficulty in distinguishing definition
low efficiency and focusing evaluation function invalid. To improve the efficiency and accuracy of automatic inspection
an automatic micro-vision detection system was developed independently to research the auto-focusing technology of the sputum smear images collection. Firstly
the sputum smear images focusing evaluation advantages and disadvantages of the eleven common focusing functions were studied comparatively
and the reasons for the image focusing failure were analyzed. According to the comprehensive performance of the various functions in the sputum smear images acquiring
an improved focusing evaluation function based on the Tenengrad focusing function was proposed. The image focusing accuracy was enhanced through adjusting the focusing weight of the content pixels
and the image processing algorithm was optimized to improve the image collection efficiency. The experimental results show that the improved Tenengrad focusing function (FTen-Q) has high sensitivity and accuracy in the images evaluation of Mycobacterium tuberculosis smear. Compared with the traditional Tenengrad function
the image focusing success rate and computing efficiency are improved by 13.884% and 17.616%
respectively
which can meet the application requirements of this kind of nonuniform smear micro-vision detecting system.
QU Y F, PU Z B, ZHAO H J, et al..Influence Factor Analysis of Sensitivity of Focus Criteria Function[J].Acta Optica Sinica, 2005, 25(7):902-906.(in Chinese)
SUN M L, ZONG G H, YU Z W, et al..Automatic focusing system of micro-vision based on image analysis[J]. Journal of Beijing University of Aeronautics and Astronautics, 2005, 31(2):192-196. (in Chinese)
ZHAI Y P, ZHOW D X, LIU Y H, et al..Design of evaluation index for auto-focusing function and optimal function selection[J]. Acta Optica Sinica, 2011, 31(4):234-244. (in Chinese)
ZHAO H, BAO G T, TAO W. Experimental research and analysis of automatic focusing function for imaging measurement[J].Opt. Precision Eng., 2004, 12(5):531-536. (in Chinese)
XU Z, CHEN Y F, SUN Q, et al..Auto-focusing in optical microscopy for machine-vision-based precise measurement[J].Opt. Precision Eng., 2016, 24(9):2095-2100. (in Chinese)
BODDEKE F R, VLIET L J V, NETTEN H, et al.. Autofocusing in microscopy based on the OTF and sampling[J]. Bioimaging, 2015, 2(4):193-203.
TENENBAUM J M. Accommodation in computer vision [M]. Stanford University, 1971.
NAYAR S K, NAKAGAWA Y. Shape from focus[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 1994, 16(8):824-831.
YANG G, NELSON B J. Wavelet-based autofocusing and unsupervised segmentation of microscopic images[C]// Ieee / rsj International Conference on Intelligent Robots and Systems. IEEE , 2003: 2143-2148 vol. 3. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1249188
VOLLATH D. Automatic focusing by correlative methods[J]. Journal of Microscopy, 1987, 147(3):279-288.
LI Y F, CHEN N N, ZHANG J C.Fast and high sensitivity focusing evaluation function[J].Application Research of Computers, 2010, 27(04):1534-1536. (in Chinese)
HONG Y Z, REN G Q, SUN J, et al..Analysis and improvement on sharpness evaluation function of defocused image[J].Opt. Precision Eng., 2014, 22(12):3401-3408. (in Chinese)
ZHAI Y P, LIU Y H, ZHOU D X, et al..Autofocusing Method for Microscopy with Low Image Content Density[J].Journal of Software, 2012, 34(05):1281-1294. (in Chinese