Abstract:
In Bangladesh fish farming is already a major source of employment and many working
facilities can be created through high-tech commercial fish farming systems. Even the
unemployed educated people can also contribute to this business and create a lucrative
business and earning opportunity for them. This “Fish Detection by Machine learning
Approach” makes our life easy and increases our knowledge about fish. This project
represents a model to detect and recognize local fishes of Bangladesh implementing image
processing and neural networking approaches. The project work aims to apply computer
vision and AI techniques so that people of the next generation can recognize Bangladeshi
fishes as most of the young people in the city, have less idea to classify traditional and desi
fishes. We implemented our custom Dataset consisting of 1250 sample images for the
experiment method to measure out its credibility. In the proposed, model a sequential
grassfire algorithm is used along with pre-processing techniques like noise cancelation,
gray scaling, flood-fill method, binarization to detect and analyze the shape of fish. Then
Further, to do classification and recognition of the detected fishes, convolutional neural
network (CNN) and method of Visual Geometry Group (VGG-16) had been applied.
