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Visual examination and interpretation of microscopic images taken from the cervix are at the core for the detection and prevention of cervical cancer. However these visual processes are tedious and in many cases error-prone. This is why automated screening systems, interacting with the technologist, would be a tremendous improvement for reducing the likelihood of human errors. In this work we propose THREECOND, a three colour-based algorithm that integrates colour information, cyto-pathologists knowledge and fuzzy systems. This algorithm is designed to be integrated into the previously developed system [23], with the aim of improving its accuracy and efficiency for detecting and segmenting the nuclei of Pap smear images.