Influence Analysis of Image Feature Selection Techniques Over Deep Learning Model

The digital images are the data storage method which stores the real world information on a matrix based on pixels. The images are now become very valuable due to increasing applications in medical, engineering, and social. Therefore, Image processing and Classification plays an essential role. In this paper, we are investigating the employment of three different features i.e., shape, color and texture for image classification. In addition, the combined feature is also used for demonstrating the impact on classifier. The Deep learning based Convolutional Neural Network is used for feature and their combination classification. In this experiment, Diabetic Retinopathy Detection dataset is used.The performance of the model is evaluated in terms of accuracy which demonstrates the feature selection techniques are able to improve the classification accuracy and also minimize the resource utilization