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Bird watching is an art of observing, studying and researching on birds. People who pursue bird watching as a hobby or passion can be termed as bird-watchers and others involved in scientific study and research on birds are termed as ornithologists. All ornithologists are bird-watchers but not all bird-watchers are ornithologists. Accurate bird-identification is an important aspect of bird-watching. In India, not many software are available that use input image for identification of a specie, thus making the identification process cumbersome for bird-watchers. To overcome this issue, we came across a solution of building software as a project. The database consisted of 300-400 different images of number of bird species. Concept of transfer learning and pre-trained algorithm made feature extraction possible from an image. The result obtained were of high efficiency as the software could easily identify a bird species from an image whose dataset was present in the database.
Keywords Image Recognition, Bird Identification, Transfer Learning, Feature Extraction, Support Vector Machine, Machine Learning, MATLAB
Many people across countries are getting into this interest of bird-watching as a hobby or extra-curricular activity. In modern world, it acts as a great stress buster and a cheap way of getting connected with nature. Another benefit of birdwatching is awareness about nature conservation by observing behavior, migratory pattern, population, and conservation status of bird species. From conservation point of view, it is important that more and more number of people turn towards bird-watching and help collect data that can be used to study birds. Sometimes, bird identification can be difficult for beginners as well as experienced bird-watchers. The focus of our project is to also simplify the identification process. As far as India is concerned, there is no bird identification software available that takes image as an input and gives the identity of the bird as output. There are bird identification software available for countries such as US and Canada (eg. eBird, Merlin Bird ID) but very few good quality bird identification software are available in India. For beginners, the software will be of great help because at the early stages of bird-watching, identifying or differentiating between different species can be difficult and frustrating. To experienced bird-watchers also this software will majorly help in identification.
The main idea behind developing the identification software is to build awareness regarding bird-watching, bird and their identification, especially birds found in India. It also caters to need of simplifying bird identification process and thus making bird-watching easier. The technology used in the experimental setup is Transfer learning in MATLAB on a pretrained algorithm (AlexNet). It uses feature extraction for image recognition. The method used is good enough to extract features and classify images. This paper presents a summary of our project. The main purpose of the project is to identify the bird species from an image given as input by the user. The technology used is transfer learning and MATLAB. We used MATLAB because it is suitable for implementing advanced algorithm and gives good numerical precision accuracy. It is also general purpose and scientific. We achieved an accuracy of 80%-85%. We believe this project extends a great deal of scope as the purpose meets. In wildlife research and monitoring, this concept can be implemented in camera traps to maintain the record of wildlife movement in specific habitat and behavior of any species.
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