Table 3. Techniques and datasets used for RBC segmentation.

The WBC segmentation techniques dataset used for WBC segmentation, along with the relevant features and image enhancement techniques commonly applied before the WBCs segmentation process.

Work	Database	Segmentation	Features	Enhancement	Classifier
Aliyu et al. (2019)	Online from ash bank and shutter stock	Otsu threshold and Binarization	Form factor, perimeter, and area	Nil	SVM
Chaudhary et al. (2019)	Nil	K-means algorithm	Perimeter and area	Nil	Nil
Tran et al. (2019)	ALL-IDB1 108 images	SegNet and VGG-16	VGG-16	Distance transform	Nil
Miao & Xiao (2018)	100 manually collected images	Marker-controlled watershed	Nil	Histogram base technique	Marker-controlled watershed
Al-Hafiz, Al-Megren & Kurdi (2018)	BBBC dataset	Threshold value using detection operator	Gradient magnitude and canny operator	Median filter	Nil
Rehman et al. (2018)	Thin blood smear images	Local maxima, circles drawing	Areas, elongation and normalize variance	Thresholding for binary conversion	Nil
Das, Maiti & Chakraborty (2018)	950 nucleated blood cells	Marker-controlled watershed algorithm	Color feature	Special Fuzzy C-mean	RFT
Imran & Ahmad (2017)	ALL-IDB1 108 images	Fuzzy C-means	Texture and geometrical	Nil	SVM
Shirazi et al. (2016c)	Nil	Snake algorithm, Ostu Thresholding	Color feature	HSV color	SVM
Alomari et al. (2014)	100 microscopy images	Thresholding	Color feature	Nil	Nil