1. A process for identifying and quantifying helminth eggs in environmental samples, from the at least one image comprising: filtering the at least one image with an anisotropic diffusion filter locating the borders on the at least one image, obtaining at least one filtered image; filtering the at least one filtered image applying at least one Laplacian of Gaussian threshold detecting changes within the at least one filtered image, obtaining at least one binarized image; processing the at least one binarized image by means of a Watershed algorithm with a filtered distance field, segmenting the at least one binarized image and extracting the boundaries in the at least one binarized image, obtaining at least one image filtered again; filtering the at least one image filtered again eliminating objects by perimeter compactness, considering the size of objects in the at least one image filtered again and separating the differences to avoid false positives, obtaining at least one image with identified objects; characterize the identified objects in the at least one image segmenting the objects by means of gray profiles; classify the characterized objects according to the statistic classifier for identifying and quantifying the type of helminth egg; and validate the result in a statistic manner.