Abstract

Age estimation based on fish otolith microstructure analysis is a very repetitive and time-consuming task. The lack of appropriate image analysis software, capable of both overlaying a number of images automatically and recording a high number of daily increments, has been a significant limitation in counting and measuring daily growth increments in large otoliths from juvenile and adult fish individuals. This paper presents a new software to assist marine biologists with faster, more efficient, and more reliable microstructure readings of fish otoliths. Open source code is preferred so that software packages can be updated with new image processing algorithms developed by the scientific community. The approach consists of three steps: 1) a single grayscale digital image combining images of different parts of the same fish otolith is obtained using the blind image registration technique fast normalized cross correlation; 2) the growth rings of the image are enhanced for age estimation purposes, using the adaptive histogram equalization technique; and 3) a semiautomatic interactive tool draws a simple polygonal chain along which the microstructures are easily identifiable and the points of interest can be marked, whose data will be saved automatically. This new tool opens up the opportunity of aging juvenile and adult fish individuals at regular intervals by counting growth rings in the otolith microstructure and facilitates working with other calcified pieces of marine species that exhibit a daily ring pattern, such as cephalopod beaks and mollusk shells.

Full Text
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