This work analyzes the morphological characteristics and fractal dimension of diesel particulate matter (DPM) produced by multipoint-intake fumigation of n-butanol in a diesel engine. A novel methodology based on digital images processing (DIP) of micrographs from transmission and scanning electron microscopy (TEM and SEM) is presented. Two DIP algorithms were developed and compared for identification and cleaning of TEM images background: the semi-automatic (supervised), which uses the Watershed transform, morphological operators and edge detectors; and the automatic (non-supervised), which further includes adaptive threshold methods. Both algorithms performed successfully when compared with manual methods allowing a significant time saving (from 12 hours manual to 2 minutes automatic). Results showed that mean primary particle diameter (dp0), mean particulates agglomerates diameter, and fractal dimension of the agglomerate (Df) of DPM, which were around 30 nm, 70 nm, and 1.9 dimension respectively, were not affected by n-butanol fumigation in comparison with Ultra-low sulfur diesel (ULSD). The algorithms were sensible to the manual selection of the primary particles from the micrographs, strongly affected the determination of total number of primary particles (np0) and its diameter of gyration (dg); but the Df is not affected. Both algorithms performed successful avoiding the user subjectivity and providing significant time saving during the analysis.