Image-Based Bird Species Identification Using Machine Learning

Along with humans, birds lead lovely lives and are amazing creatures. One of the signs of climatic change is birds. From mid-level consumers to top predators, birds play a significant role in all trophic levels. Currently, extinction threatens many of these bird species. Naturally, each bird is unique in terms of its traits as well as its physical attributes, including shape, size, beak, feathers, silhouette, and others. As opposed to audio-based classification, bird photos are particularly useful in identifying species. By far, the most comfortable method for humans to identify birds is by visual classification. One of the crucial components of image categorization is the dataset of birds, which has been gathered. From the input image, the features are retrieved, and then classification is performed. Both regression and classification are performed using the Random Forest method. To create autographs using tensor flow, the input image is first transformed to grayscale and then to matrix format. As a consequence, the characteristics of the provided bird image are extracted, the bird’s name is determined, and the bird’s origin is also shown.