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ISSN 2063-5346
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Dove Species Categories Classification based on Image Processing and Machine Learning Techniques

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Sulaya Betsabe Bayancela-Delgadok,Omar Rolando Quimbita Chiluisa,Coello-Cabezas Julio,Danny Alexander Rivas Sierra,Byron Oviedo
» doi: 10.48047/ecb/2023.12.5.180

Abstract

In this research papers it study about the classification of dove species using machine language and image processing technique. Now a day Image Processing Technique is an advance technology for detail analysis and classification of birds’ species to achieve advance result with unique qualities. In this paper the method is broadly categories into the following stages such as preprocessing stage, segmentation stage, feature extraction and K-Nearest Neighbor classifier. This investigation contains 70% for training data and 30% for testing data using dove species images. For investigations the doves species image collected is 200 images during analysis. The dataset used dove images with three classes such as accuracy of mourning dove species, accuracy of European turtle dove species, and accuracy of spotted dove species. The present investigation results that SYMLET5 analysis works well in the classification of the dove species with accuracy of 97% using K- Nearest Neighbor classifier compare with other measures.

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