De la Fuente, Maricris I. creator author. Felices, Farah Faye P. author Medrano, Mae Z. author Naldo, Ian Jake A. author Portea, Tom Jairus V. author Tabal, Keith Marlon R., technical adviser Terano, Harold Jan R., chair, panelist Isaac, Victor Solito Dr., panelist Cerillo, Jose Eduardo B., panelist text bibliography ph 2022 monographic eng

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172 leaves This research project developed a counting system for Tilapia fingerlings by incorporating Otsu thresholding and Morphological Transformations algorithms in the system design. The different processes and technique procedure of fingerling counting for both the traditional and automatic counting methods were considered in the study and a number of image processing algorithms used in existing fish counters were explored. The existing systems usually require sophisticated hardware and computers that adds up to the cost of manufacturing. The present work used a Raspberry Pi 4 B Single Board Computer and Raspberry Pi Camera Module v1.3 to lessen the cost using computer vision and image processing algorithms calculated through a Confusion Matrix. The system prototype was designed for the three different sizes of tilapia fingerlings: Direkta, Potential and Oversized. However, it was only tested for the Direkta fingerlings. Moreover, the performance of the system was evaluated in terms of accuracy and speed of the device. The results implies that the automatic counting system developed by the project is a faster and more consistent method for counting tilapia fingerlings than the manual counting process, particularly for larger batch sizes. Maricis I. de la Fuente [and 4 others]. Undergraduate Theses (BSECE) - Electronics Engineering. Camarines Sur Polytechnic Colleges, 2022. Includes bibliographical references. CSPC 240301 20240301142739.0 eng