The main goal of the work done by the Biomedical Engineering Research Group (GIIB), and the Structural, Functional and Clinical Pathology Research Group of the Industrial University of Santander (UIS), with Autonomous University of Bucaramanga (UNAB), was to construct a computational model allowing squamous cells characterization of cervical smear cytology to classify them as being either normal or abnormal cells. Slides containing the cell samples were colleted by the pathologist and the images were digitalized by a video-camera coupled to a microscope and connected to a frame acquisition device. Three thresholding algorithms were used, in image segmentation, allowing cell nuclei detection; manual thresholding was used when these algorithms failed to detect cytoplasm. Cell texture was described by the distribution of histogram in each color level, and the borders using Fourier descriptors. The results of the first phase are presented, implementing them in classifying and identifying normal cells. Later stages will involve