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Industrial inspection of micro-devices is often a very challenging task, especially when those devices are produced in large quantities using micro-fabrication techniques. In the case of microlenses, millions of lenses are produced on the same substrate, thus forming a dense array. In this article, we investigate a possible automation of the microlens array inspection process. First, two image processing methods are considered and compared: reference subtraction and blob analysis. The criteria chosen to compare them are the reliability of the defect detection, the processing time required per frame, as well as the sensitivity to image acquisition conditions, such as varying illumination and focus. Tests performed on a real-world database of microlens array images led to select the blob analysis method. Based on the selected method, an automated inspection software module was then successfully implemented. Its good performance allows to dramatically reduce the inspection time as well as the human intervention in the inspection process.