Detection Method for the Center of Touching Particle Image

doi:10.15888/j.cnki.csa.006048

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Home > Archive>Volume 26, Issue 9, 2017 >181-187. DOI:10.15888/j.cnki.csa.006048

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Detection Method for the Center of Touching Particle Image
DOI:
                        10.15888/j.cnki.csa.006048
                    
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                        YE MingYE Ming
College of Mechanical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
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WU Di-FeiWU Di-Fei
College of Mechanical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
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Abstract:

Aiming at the problem of detecting the centers of touching particles images, a detecting method based on the improved Generalized Hough transform is proposed in this paper. The method firstly figures out the ring that overlaps the known particle's outline, then the overlapping area of the ring template is accumulated along the foreground contour of the image to be detected. Finally, the region maximum value of the accumulated matrix will be the centers of the particles. The ring template has rotation invariance so that the detection time will be shortened greatly. Meanwhile, the result shows that the method in this paper has fine detection effect.

Key words:touching particles;the Generalized Hough transform;foreground makers

Reference

[1] Farhan M, Yli-Harja O, Niemistö A. A novel method for splitting clumps of convex objects incorporating image intensity and using rectangular window-based concavity point-pair search. Pattern Recognition, 2013, 46(3):741-751.[DOI:10.1016/j.patcog.2012.09.008]

[2] Kumar S, Ong SH, Ranganath S, et al. A rule-based approach for robust clump splitting. Pattern Recognition, 2006, 39(6):1088-1098.[DOI:10.1016/j.patcog.2005.11.014]

[3] 韦冬冬, 赵豫红. 基于凹点匹配的重叠图像分割算法. 计算机与应用化学, 2010, 27(1):99-102.

[4] 倪志强, 叶明. 基于分水岭变换的粘连颗粒图像分割方法. 计算机系统应用, 2014, 23(6):93-97.

[5] 戴丹. 基于改进分水岭算法的粘连颗粒图像分割. 计算机技术与发展, 2013, (3):19-22.

[6] Meyer F, Beucher S. Morphological segmentation. Journal of Visual Communication and Image Representation, 1990, 1(1):21-46.[DOI:10.1016/1047-3203(90)90014-M]

[7] 刘相滨, 邹北骥, 孙家广. 菌群细胞图像分离算法研究. 电子学报, 2005, 33(6):1056-1059.

[8] 李希, 王天江, 周鹏. 一种改进的粘连颗粒图像分割算法. 湖南大学学报(自然科学版), 2012, 39(12):84-88.[DOI:10.3969/j.issn.1674-2974.2012.12.015]

[9] 李智磊, 翟宏琛, 王明伟. 一种可识别破碎图形的特殊广义Hough变换方法. 物理学报, 2007, 56(6):3234-3239.[DOI:10.7498/aps.56.3234]

[10] 胡正平, 杨苏. 基于关键特征点决策的广义Hough变换目标定位快速算法. 信号处理, 2009, 25(11):1748-1753.[DOI:10.3969/j.issn.1003-0530.2009.11.016]

[11] 刘宏申, 程健. 广义Hough变换算法的分析改进. 中国科学技术大学学报, 2009, 39(11):1202-1206.

[12] Kontschieder P, Riemenschneider H, Donoser M, et al. Discriminative learning of contour fragments for object detection. Proc. of the British Machine Vision Conference. Dundee, UK. 2011.

[13] Gall J, Lempitsky V. Class-specific Hough forests for object detection. 2013 IEEE Conference on Computer Vision and Pattern Recognition. Miami, FL, USA. 2009. 1022-1029.

[14] Opelt A, Pinz A, Zisserman A. A boundary-fragment-model for object detection. Computer Vision-ECCV 2006, 9th European Conference on Computer Vision. Graz, Austria. 2006. 575-588.

[15] Xu L, Oja E, Kultanen P. A new curve detection method:Randomized Hough transform (RHT). Pattern Recognition Letters, 1990, 11(5):331-338.[DOI:10.1016/0167-8655(90)90042-Z]

[16] Tsai DM. An improved generalized Hough transform for the recognition of overlapping objects. Image and Vision Computing, 1997, 15(12):877-888.[DOI:10.1016/S0262-8856(97)00033-4]

[17] 杨华, 尹周平, 王瑜辉, 等. 基于局部不变几何特征的广义霍夫变换图像匹配方法:中国, CN103456005A.[2013-12-18].

[18] 侯怡婷. 基于CUDA的Hough变换并行实现[硕士学位论文]. 大连:大连理工大学, 2013.

[19] 尹平平. 喷丝板微孔中熔体流动及异形纤维成形过程的研究[硕士学位论文]. 上海:东华大学, 2006.

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叶明,吴迪飞.一种粘连颗粒图像中心点的识别方法.计算机系统应用,2017,26(9):181-187

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Received:December 29,2016
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Online: October 31,2017
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