Abstract
We present the real-time flow imaging and classification system (REFLICS), a real-time machine vision system for detecting and classifying pelagic fish eggs (e.g. sardine, anchovy) flowing through a shipboard pumping and filtering system. REFLICS images the dynamic flow with a progressive-scan area camera and a synchronized backlight strobe. Digitization and processing occur on a dual processor Pentium II PC and a pipeline image processing board. REFLICS first uses a segmentation algorithm to locate fish egg-like objects in the image and then a classifier to determine fish eggs, species and development stages (ages). We present the integrated system design of REFLICS and performance results. REFLICS can perform in 60 Hz real-time, classify fish eggs with low false negative rates on data collected from real cruises, and work in harsh conditions aboard ships at sea. REFLICS allows more accurate and timely survey of fish stock in a cost-effective manner.
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