In this study, human fecal parasite detection technique based on Filtration and Steady Determinations Thresholds System ( F-SDTS ) was proposed. The recognition method includes three stages. First stage, a preprocessing subsystem is realized for obtaining unique features after performing noise reduction, contrast enhancement, segmentation and other morphological process are applied for feature extraction stage of F-SDTS approach. Second stage, a feature extraction mechanism which is based on five features of the three characteristics (shape, shell smoothness, and size) is used. Third stage, Filtration with Steady Determinations Thresholds System ( F-SDTS ) classifier is used for recognition process using the ranges of feature values as a database to identify and classify the type of parasite. The technique enables to classify two different parasite eggs from their microscopic images which are roundworms (Ascaris lumbricoides ova, ALO) and whipworms (Trichuris trichiura ova, TTO). Finally, simulation result shows overall success rates are almost 93% and 94% in Ascaris lumbricoides and Trichuris trichiura, respectively.
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