A common hobby that provides relaxation from daily life is bird watching. In nature, birds are present. They support the environment and ecosystem. Given how visually similar many bird species are, it is a difficult challenge. As a practical aid for birdwatchers to recognize the species in their native habitat, for humans, it might be difficult to identify different bird species. From a human perspective, it is only natural for birds to appear in a variety of situations in a variety of sizes, shapes, colors, and perspectives. Some bird species are now only sometimes discovered, and even then, it can be challenging to classify them. Additionally, photos offer more distinct variants for bird species identification than audio categorization. The ability of humans to identify the birds from the images is also easier to understand. To identify the species from one another, shape feature is important. Edge detection is a key component of shape extraction. Edge is a significant visual feature that uses a limited number of pixels to communicate visual information. Because of climate factors, it can be uncertain to assess a bird's morphology. Therefore, in this study, we used the Bird Image Edge Detection using Fuzzy Algorithm (BIEDF) to implement this model to extract data from bird images.