Abstract

Morphological characters have commonly been used in analysis of biological contexts. Researchers often use the arrangements of morphological landmarks in their studies to extract shape information from any biological materials and need to get bio-measurements using any computer aided tools. Getting landmarks and measurements from biological materials are a time-consuming process. Hence, this study is to provide an intelligent integrated software called BioMorph for morphological measurements. With the BioMorph, Family and species identification of a studied bio-object are automatically be determined using artificial neural network and k-nearest neighbor. The landmarks for discrimination of the bio-objects are automatically found from the given image using artificial neural network. In addition, network analysis methods such as the Euclid network distances, Truss network distances, Triangular network distances, some statistical measures such as mean, standard deviation, minimum and maximum values, etc. and image processing techniques such as image editing, image filtering, image segmentation, etc. are also integrated to the BioMorph.