<p>Cutting forces and global chip morphology are often utilized as comparison parameters for validating numerical simulations of machining. Geometrical chip features are less utilized for comparisons because their measurement is tedious. Currently, serrated chips characteristics, such as peaks and valleys heights, are <i>manually measured</i>. The aim of this study is to propose an <i>automated measurement</i> of serrated chips features, using image processing algorithms. These are applied to images taken from video recordings of orthogonal cutting of Ti6Al4V titanium alloy. The first step of the algorithm consists in images pre-processing for edges detection, artifacts removal and applying some morphological transformations. For measurements of chips features, a succession of four steps is done: (i) detection of the outer surface of the chip; (ii) reconstruction of the inner surface of the chip; (iii) suppression of artifacts in chip thickness measurements and (iv) search for local thickness extremums to find chip peaks and valleys heights. To assess the algorithm accuracy, around 210 individual chips segments are manually annotated on images of orthogonal machining. This made it possible to compare each measurement carried out automatically by the program with the corresponding manual measurement. The developed program showed a good accuracy in measuring maximum chip thickness under all cutting conditions investigated in this study, exhibiting a maximum deviation of 4%. It overestimates the minimum chip thickness by up to 26%; however, this discrepancy could be reduced through enhancements in the algorithms employed during the image pre-processing stage, as well as through improvements in image quality.</p>