Otary now includes 17 image binarization methods

Summary

class BinarizerImage: # pylint: disable=line-too-long """BinarizerImage class contains all the binarization methods. It includes only two global thresholding methods: `threshold_simple` and `threshold_otsu`. The other methods are local thresholding methods. It includes the following binarization methods, sorted by year of publication: | Name | Year | Reference | |----------------|------|------------------------------------------------------------------------------------------------------------------------------------------| | Adaptive | - | [OpenCV Adaptive Thresholding Documentation](https://docs.opencv.org/4.x/d7/d4d/tutorial_py_thresholding.html) | | Otsu | 1979 | [A Threshold Selection Method from Gray-Level Histograms](https://ieeexplore.ieee.org/document/4310076) | | Bernsen | 1986 | "Dynamic thresholding of grey-level images" by Bernsen | | Niblack | 1986 | "An Introduction to Digital Image Processing" by Wayne Niblack | | Sauvola | 1997 | [Adaptive Document Binarization](https://www.researchgate.net/publication/3710586_Adaptive_Document_Binarization) | | Wolf | 2003 | [Extraction and Recognition of Artificial Text in Multimedia Documents](https://hal.science/hal-01504401v1) | | Feng | 2004 | [Contrast adaptive binarization of low quality document images](https://www.jstage.jst.go.jp/article/elex/1/16/1_16_501/_pdf) | | Gatos | 2005 | [Adaptive degraded document image binarization](https://users.iit.demokritos.gr/~bgat/PatRec2006.pdf) | | Bradley & Roth | 2007 | [Adaptive Thresholding using the Integral Image](https://www.researchgate.net/publication/220494200_Adaptive_Thresholding_using_the_Integral_Image) | | Nick | 2009 | [Comparison of Niblack inspired Binarization Methods for Ancient Documents](https://www.researchgate.net/publication/221253803) | | Su | 2010 | [Binarization of historical document images using the local maximum and minimum](https://www.researchgate.net/publication/220933012) | | Phansalkar | 2011 | [Adaptive Local Thresholding for Detect...