Image synthesis method based on multi-feature fusion

Abstract

The invention relates to an image synthesis method based on multi-feature fusion. The method is used for synthesizing pictures into a portrait or synthesizing portraits into a picture. The method includes the steps of dividing a database sample set, blocking images and extracting features of image blocks after image filtering is carried out on all images to obtain a training portrait block dictionary and a picture block dictionary, finding adjacent blocks by means of the two dictionaries according to input test picture blocks or test portrait blocks, building a markov network model to obtain portrait blocks to be synthesized or picture blocks to be synthesized, and fusing all portrait blocks to be synthesized or picture blocks to be synthesized to obtain the synthesized portrait or the synthesized picture. Compared with the prior art, definition of a synthesized result is higher, structure loss is less, and the method can be used for facial retrieval and recognition.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to an image synthesis method based on multi-feature fusion in the technical field of pattern recognition and computer vision, which can be used for face retrieval and recognition in criminal investigation and case solving. Background technique [0002] With the development of science and technology, how to accurately identify and authenticate a person's identity has become one of the urgent problems to be solved. Among them, face recognition has the characteristics of directness, friendliness and convenience, and has been widely researched and applied. . An important application of face recognition technology is to assist the police in case detection. However, in many cases, it is difficult to obtain photos of suspects. The police can draw a portrait of the suspect based on the descriptions of witnesses at the scene, and then search and identify them in the police ph...

AI Technical Summary

Problems solved by technology

However, the disadvantage of this method is that because the number of neighbors is fixed, the synthesis result has defects of low definition and blurred details.

However, the disadvantage of this method is that only one training image block is selected for each photo block position for image synthesis, resulting in block effects and missing details in the synthesis results.

However, the disadvantage of this method is that it ignores the relationship between adjacent image blocks, resulting in blurring and block effects in the synthesis results.

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