Automated image analysis procedures combined with discriminant factorial analysis (DFA) have been developed to classify agglomerated sucrose crystals according to their shape. The crystals are observed by optical microscopy. Agreement between manual and automated classifications is 90% in average. Each crystal is characterised by its own degree of agglomeration, calculated from the output of the classification. Mono-crystals are further classified into two types according to the habit of their projected silhouette. The use of these techniques is illustrated on commercial sucrose and batch-crystallised particles obtained in a lab-scale reactor in presence of impurities (dextran, raffinose, glucose, sodium carbonate) known to modify the sucrose crystal habit. (C) 2003 Elsevier Science B.V. All rights reserved.