Automated Bird Species Recognition System Based on Image Processing and Svm Classifier

• Published in: Turkish journal of computer and mathematics education 2021-04, Vol.12 (2), p.351-356
• Main Authors: Chandra, B, Raja, S Kanaga Suba, Gujjar, R Vignesh, Varunkumar, J, Sudharsan, A
• Format: Article
• Language: English
• Subjects: Algorithms; Birds; Cameras; Classification; Image classification; Image processing; Machine learning; Object recognition; Species classification; Support vector machines; Teaching Methods
• ISSN: 1309-4653; 1309-4653
• DOI: 10.17762/turcomat.v12i2.813

Here, in this study we can learn about Bird species recognition. In forest areas cameras are fixed at various locations which capture images periodically. From those images the birds living in such dense forest areas can be identified. It would be useful if we can able to classify the species of birds with the help of those images. But that is not an easy task because of the variations in the light effects, illumination and camera viewpoints. So we need to involve image processing techniques for preprocessing the captured image and also deep learning techniques are to be implemented for classifying the images. For classification purpose training is to be done with the help of image data set. Here we propose a method of discriminating birds by means of the ratio of the distance between eye and beak to that of the beak width. By combining this mythology with image processing and SVM classification technique a new bird species recognition algorithm is proposed. The proposed new methodology will improve the accuracy in classifying.