Abstract: Inter-disciplinarity has been responsible for solving several problems in the medical areas, being that many of which are derived from the use of engineering techniques. One problem that affects a large part of the world's population is the difficulty of access to health, often caused by a lack of financial resources. One of the most requested medical tests due to its ability to detect a wide range of diseases is the hemogram. However, this methodology is often inaccessible due to its cost, which for disadvantaged populations can be seen as high. Based on this, the present study aims to develop an algorithm for the segmentation of digital images of blood smears, which is capable of detecting and counting erythrocytes, leukocytes and platelets simultaneously, with high accuracy and low cost. The algorithm was developed in the Matlab software environment, based on the Watershed Transform, Transformed Hough methodologies and operations methodologies. The hybrid algorithm was named WHT-MO. The experiments were conducted using 10 digital blood smear images. The results showed high accuracy (90% and 100%) in the detection of the three cell types. Therefore, the WHT-MO algorithm demonstrates that the hemogram can be performed using a simple computer, dispensing with the need to acquire high-cost hematological equipment, which directly impacts the final price of the examination for patients. In addition, high accuracy demonstrates that it is possible to perform the hemogram at a reduced cost without loss of quality and reliability Ver menos