Tilapia (oreochromis niloticus) fingerling counting system / Maricis I. de la Fuente [and 4 others].
Material type:
TextDescription: 172 leavesContent type: - text
- unmediated
- volume
| Item type | Current library | Shelving location | Call number | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|---|
Unpublished Materials
|
Main Library | Undergraduate Thesis Section | UTH BSECE D3703t 2022 (Browse shelf(Opens below)) | Not for loan | 006143UM |
Browsing Main Library shelves, Shelving location: Undergraduate Thesis Section Close shelf browser (Hides shelf browser)
| No cover image available | No cover image available | No cover image available | No cover image available | No cover image available | No cover image available | No cover image available | ||
| UTH BSECE D338m 2002 Multifunction combination switch/ | UTH BSECE D355o 2006 The on-the-job training of the electronics and communication engineering students in CSPC/ | UTH BSECE D365w 2009 Wireless basketball scoreboard/ | UTH BSECE D3703t 2022 Tilapia (oreochromis niloticus) fingerling counting system / | UTH BSECE D379a 2022 Assessment of electromagnetic radiation of selected cellular base stations in Rinconada | UTH BSECE D379d 2022 Development of a measuring device for drinking water quality | UTH BSECE D379d 2022 Development of an android-bassed emergency alert system |
Undergraduate Theses (BSECE) - Electronics Engineering. Camarines Sur Polytechnic Colleges, 2022.
Includes bibliographical references.
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.
There are no comments on this title.