Image analysis is a fast evolving field of research because the image acquisition technology and processing algorithms develop constantly. The possible fields of application are becoming larger and more diverse in various application sectors from the automotive to the medical industry. Within in the presented work, the enormous potential of image analysis in crystallization is demonstrated. A detailed analysis of size, shape and texture can be performed to quantify the product quality and identify optimized process conditions and procedures with low effort. Various application examples are presented that examine important quality attributes that contribute to the purity of the final product. With a specific selection of the image acquisition methods and sophisticated image processing, including deep learning approaches, crystal defects and agglomeration can be quantified. For agglomeration inline measurements coupled with short-cut modeling, even enable tracking and evaluating the phenomenon and its influencing factors directly in the process.