Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Consider a natural image that has been manipulated by copying, transforming and pasting back fragments of the image itself. Our goal is to detect such manipulations in the absence of any knowl- edge about the content of the repeated fragments or the transformations to which they might have been subject. The problem is non-trivial even in the absence of any transformations. For example, copy/paste of a tex- tured fragment of a background can be difficult to detect even by visual inspection. Our approach to the problem is a two-step procedure. The first step consists in extracting features from the image. The second step explores the connection beten image compression and complexity: a finite-context model is used to build a complexity map of the image features. Patterns that reappear, even in a somewhat modified form, are encoded with fer bits, a fact that renders the detection of the repeated regions possible.
['Paulo Jorge S. G. Ferreira', 'Armando J. Pinho']
I am writing a research paper on a idea A Method to Detect Repeated Unknown Patterns in an Image
[{"from": "human", "value": "I am writing a research paper on a idea A Method to Detect Repeated Unknown Patterns in an Image"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Consider a natural image that has been manipulated by copying, transforming and pasting back fragments of the image itself. Our goal is to detect such manipulations in the absence of any knowl- edge about the content of the repeated fragments or the transformations to which they might have been subject. The problem is non-trivial even in the absence of any transformations. For example, copy/paste of a tex- tured fragment of a background can be difficult to detect even by visual inspection. Our approach to the problem is a two-step procedure. The first step consists in extracting features from the image. The second step explores the connection beten image compression and complexity: a finite-context model is used to build a complexity map of the image features. Patterns that reappear, even in a somewhat modified form, are encoded with fer bits, a fact that renders the detection of the repeated regions possible."}]