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Abstrak :
Clustered Red Blood Cells are observed very frequently in the thin blood smear digital images. Separating clustered Red Blood Cells from the single Red Blood Cells and splitting of clustered Red Blood Cells into single Red Blood Cells is a challenging job in the computer-assisted diagnosis of blood for any disorder in many diseases like Complete Blood Count Test, Anemia, Leukemia and Malaria etc. The mentioned problems are highly laborious in manual microscopy for the hematologists. Many techniques currently existing for the solution suffer from both under- and over- splitting problems when highly complex clusters of Red Blood Cells occur. In addition, the existing techniques are not computationally efficient. In this paper, we address the aforementioned problems, firstly by considering the boundaries of the convex hulls of clustered Red Blood Cells and secondly, by splitting the boundaries according to the number of Red Blood Cells in relation to distance measures. Furthermore, we draw circles using a mid-point circle algorithm at each boundary cleavage to give an illusion of the Red Blood Cells. The test results of the proposed technique on a standard online dataset are presented in two ways. Statistically first of all by achieving an average recall of 0.964 and precision of 0.970 while their F-measure achieved is 0.962 as well as secondly through ground truth data with visual inspections.

Abstrak :
Over the past century, technology has made it possible to measure human motion in many ways and with new levels of precision, becoming a tool in many applications and professional branches including medicine, sports science and forensics. Some branches have developed in response to the technology, such as the emergence of motion-capture animation in the film industry. These different applications use the same or similar types of equipment with the general intention of making the systems as intuitive as possible for the participants. However, the methodologies necessary to produce reliable results in these areas differ enormously. The overlap of information between fields might lead to situations where small but important adaptations are required in order to produce the required result; experts with knowledge of one field might not be aware of such developments. The Handbook of Human Motion brings together contributions from many different disciplines, covering the established and emerging technologies employed, the challenges posed in each area of application and the novel solutions reached by researchers.