I MAS Framework For Image Plagarism Detection in System Architectures (Image Multi-Agent System)

ABSTRACT Image Plagiarism has been overlooked while evaluating research articles. Most intelligently adopted plagiarism pattern copying text as image in research articles. Architecture diagrams have been copied from one research article to other completely or in forged way. Commonly architecture design and system overview diagrams have been plagiarized in partially or completely. Detecting image plagiarism is challenging task as image morphology is complex. Exiting image forgery detection system detects common patterns like resizing ,cut paste. Proposed system is designed on Image Multi-Agent Framework, assisting decision support in detecting intelligent plagiarism patterns for system architectures. Four phase algorithmic procedure with layer architecture are innovations of system. Correlation similarity enhances system output