Author : Kanika 1
Date of Publication :31st July 2021
Abstract: The image processing tool has attained a lot of attention. Thus, people are capable of manipulating the digital image in quick and easy manner without any obvious traces. The integrity and authenticity of digital images must be determined. The forgery is generated in two ways namely copy-move and splicing. The image blind detection has various phases which include pre- processing, feature extraction and classification. In this research work, GLCM algorithm is used for the textural feature extraction. The artificial bee colony algorithm is applied which can optimize the detected forgery pixels. The hybrid classification method is used for the classification. The hybrid classification method will be the combination of KNN, SVM and decision tree. It is expected that accuracy, precision and recall will be improved for the image blind detection.
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