This work proposes an algorithm for the detection of the intestinal parasite Giardia Lamblia from digital images obtained through a digital camera and an optical microscope. Its purpose is to reduce the time of visual inspection analysis of the sample made by the specialist in laboratory. The proposed algorithm converts the acquired RGB images to the HSV colour space. First, the saturation component is filtered using a Gaussian filter, in order to reduce the noise and standardize the areas of interest. The filtered image is thresholdized using a fixed threshold value, in order to segment the objects of interest. Then, using a labelling algorithm, a filtering is performed by object size, in order to eliminate those that do not comply with the dimensions of the parasite. Therefore, the edges are highlighted by a Canny filter, to finally apply the Hough transform and detect the morphology of the object and its physical dimensions. With this information it will be possible to validate if the object satisfies the conditions of a Giardia Lamblia parasite. The proposed method achieved a specificity of 86% and a sensitivity of 67%, processing each image in an average time of less than 2 seconds. The results were obtained from a universe of 30 images.