Estimating fish growth in real time has many benefits forindoor aquaculture farms, such as saving labor time andcosts, reducing water pollution during feeding, improvingfeeding activity and determining when to harvest. Hence,this study proposed a visual-information-based method formeasuring olive flounder (Paralichthys olivaceus) length,using accurate growth tracking for efficient aquaculturemanagement. Using two cameras, an light-emitting-diode(LED) grid was placed at the bottom of the water tank tomeasure fish length. The pixels unit from the fish length inthe captured image was converted to centimeters based onthe relationship of a pre-built dataset. A total of 180 lengthswere calculated using images captured by the cameras. Theaverage length of each fish acquired from the cameras wascalculated separately, and Lagrange's interpolating polyno-mial algorithm was implemented to calculate the overalllength of each fish. This method reduced the computationalcomplexity, and results were obtained more rapidly and in auser-friendly environment.