Image processing and analysis techniques have drawn increasing attention since they enable a non-extractive and non-lethal approach to fisheries survey, such as fish size measurement, abundance prediction, catch estimation and compliance, species recognition and population counting. In this work, we present an innovative and effective method for measuring the chute-based fish length based on the morphological midline of the fish. The midline is generated through recursive morphological operations on the segmented fish mask. To conduct reliable measurement, even under harsh environment, we also propose a systematic method for detecting water drop on camera lens. The robust detection, which can be performed either in real-time or in offline processing, is based on a blur measure derived from the gradient of the image and the contour of fish.