Toward reliable experiments on the performance of Connected Components Labeling algorithms

The problem of labeling the connected components of a binary image is well defined, and several proposals have been presented in the past. Since an exact solution to the problem exists, algorithms mainly differ on their execution speed. In this paper, we propose and describe YACCLAB, Yet Another Connected Components Labeling Benchmark. Together with a rich and varied dataset, YACCLAB contains an open source platform to test new proposals and to compare them with publicly available competitors. Textual and graphical outputs are automatically generated for many kinds of tests, which analyze the methods from different perspectives. An extensive set of experiments among state-of-the-art techniques is reported and discussed.

[1]  Wichian Premchaiswadi,et al.  Efficient scan mask techniques for connected components labeling algorithm , 2011, EURASIP J. Image Video Process..

[2]  Anil K. Jain,et al.  Handbook of Fingerprint Recognition , 2005, Springer Professional Computing.

[3]  Rita Cucchiara,et al.  3DPeS: 3D people dataset for surveillance and forensics , 2011, J-HGBU '11.

[4]  Costantino Grana,et al.  Historical Handwritten Text Images Word Spotting Through Sliding Window HOG Features , 2017, ICIAP.

[5]  Federico Bolelli.  Indexing of Historical Document Images: Ad Hoc Dewarping Technique for Handwritten Text , 2017, IRCDL.

[6]  Luigi di Stefano,et al.  A simple and efficient connected components labeling algorithm , 1999, Proceedings 10th International Conference on Image Analysis and Processing.

[7]  Shlomo Argamon,et al.  Complex document information processing: prototype, test collection, and evaluation , 2006, Electronic Imaging.

[8]  Bertrand Zavidovique,et al.  Light Speed Labeling for RISC architectures , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[9]  Chung-Cheng Chiu,et al.  Block-Based Connected-Component Labeling Algorithm Using Binary Decision Trees , 2015, Sensors.

[10]  Chung-Cheng Chiu,et al.  An efficient scan algorithm for block-based connected component labeling , 2014, 22nd Mediterranean Conference on Control and Automation.

[11]  Matti Pietikäinen,et al.  Adaptive document image binarization , 2000, Pattern Recognit..

[12]  Tianxu Zhang,et al.  Stripe-based connected components labelling , 2010 .

[13]  Kesheng Wu,et al.  Two Strategies to Speed up Connected Component Labeling Algorithms , 2005 .

[14]  Robert E. Tarjan,et al.  Efficiency of a Good But Not Linear Set Union Algorithm , 1972, JACM.

[15]  Lionel Lacassagne,et al.  Parallel Light Speed Labeling: an efficient connected component algorithm for labeling and analysis on multi-core processors , 2018, Journal of Real-Time Image Processing.

[16]  Mark J. Huiskes,et al.  The MIR flickr retrieval evaluation , 2008, MIR '08.

[17]  Kesheng Wu,et al.  Fast connected-component labeling , 2009, Pattern Recognit..

[18]  Edsger W. Dijkstra,et al.  A Discipline of Programming , 1976 .

[19]  Kenji Suzuki,et al.  Configuration-Transition-Based Connected-Component Labeling , 2014, IEEE Transactions on Image Processing.

[20]  Shlomo Argamon,et al.  Building a test collection for complex document information processing , 2006, SIGIR.

[21]  Costantino Grana,et al.  Optimal decision trees for local image processing algorithms , 2012, Pattern Recognit. Lett..

[22]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[23]  Kenji Suzuki,et al.  A Run-Based Two-Scan Labeling Algorithm , 2008, IEEE Transactions on Image Processing.

[24]  Kesheng Wu,et al.  Optimizing two-pass connected-component labeling algorithms , 2009, Pattern Analysis and Applications.

[25]  Alexei A. Efros,et al.  Unbiased look at dataset bias , 2011, CVPR 2011.

[26]  Rita Cucchiara,et al.  Optimized Block-Based Connected Components Labeling With Decision Trees , 2010, IEEE Transactions on Image Processing.

[27]  Lionel Lacassagne,et al.  Light speed labeling: efficient connected component labeling on RISC architectures , 2011, Journal of Real-Time Image Processing.

[28]  Costantino Grana,et al.  XDOCS: An Application to Index Historical Documents , 2018, IRCDL.

[29]  Kenji Suzuki,et al.  A Linear-Time Two-Scan Labeling Algorithm , 2007, 2007 IEEE International Conference on Image Processing.

[30]  Andrew H. Beck,et al.  Computational Pathology to Discriminate Benign from Malignant Intraductal Proliferations of the Breast , 2014, PloS one.

[31]  Takuji Nishimura,et al.  Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator , 1998, TOMC.

[32]  Costantino Grana,et al.  Optimized Connected Components Labeling with Pixel Prediction , 2016, ACIVS.

[33]  Chun-Jen Chen,et al.  A linear-time component-labeling algorithm using contour tracing technique , 2004, Comput. Vis. Image Underst..