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Image processing comes with various techniques. It uses a series of framework to transform an input image into an output image. In recent times, image processing technique has been extensively used in medical area. In order to overcome the problems of manual diagnosis in identifying the morphology of blood cells, the automated diagnosis is often used. Manual diagnosis required the observation of blood sample by expert hematologist and pathologist. This method may suffer from the presence of non-standard precision of human visual inspection. Due to this problem, this paper focused on semi-automated diagnosis that used image processing technique to perform the segmentation of the nucleus in white blood cell (WBC). Several image processing techniques are used including the active contour method. The results obtained are based on the parameter values obtained from segmentation process. The parameter value is calculated from the roundness equation. The value of 0.80 can be used to describe as a single leukocyte.

Whilst laboratory-on-chip cell separation systems using dielectrophoresis are increasingly reported in the literature, many systems are afflicted by factors which impede "real world" performance, chief among these being cell loss (in dead spaces, attached to glass and tubing surfaces, or sedimentation from flow), and designs with large channel height-to-width ratios (large channel widths, small channel heights) that make the systems difficult to interface with other microfluidic systems. In this paper, we present a scalable structure based on 3D wells with approximately unity height-to-width ratios (based on tubes with electrodes on the sides), which is capable of enriching yeast cell populations whilst ensuring that up to 94.3% of cells processed through the device can be collected in tubes beyond the output. V C 2013 AIP Publishing LLC. [http://dx