Face identification method suitable for psychology

Abstract

The invention belongs to the field of face identification technology, and discloses a face identification method suitable for psychology. The method comprises the steps of performing image acquisitionfor obtaining a high-definition image; performing identification on the high-definition image and performing segmentation for obtaining a face image; processing the face image which is segmented by asegmenting module; generating a to-be-identified characteristic vector of a face detail characteristic; pre-storing the characteristic vector of a known face through a face characteristic database module; performing matching calculation on the output to-be-identified characteristic vector with all characteristic vectors in the characteristic database, and outputting an identity result which corresponds with the to-be-identified characteristic vector; displaying acquired image information and matching result information. According to the method of the invention, the face characteristic database is constructed through the face characteristic database module; quick matching is performed through a characteristic matching module, thereby realizing real-time identification to identity of the to-be-identified face image on a system with limited calculating resource, and realizing short time consumption and high accuracy.

Description

technical field [0001] The invention belongs to the technical field of facial recognition, and in particular relates to a facial recognition method suitable for psychology. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: [0003] Facial recognition --- facial recognition is also known as face recognition, face recognition, face recognition, etc., facial recognition uses a general-purpose camera as an identification information acquisition device. The facial image of the recognition object is obtained in a non-contact manner, and the computer system completes the recognition process after comparing the obtained image with the database image. However, the existing face recognition is inaccurate for facial image extraction, which affects the accuracy of face recognition; meanwhile, face recognition is inefficient and time-consuming. [0004] The cognition and understanding of graphics is an important basis for...

AI Technical Summary

Problems solved by technology

Although a certain degree of efficiency has been achieved, there are still some shortcomings: the matching of the algorithm implementation process and visual resolution is not intuitive; the algorithm is complex, resulting in a large amount of data processing and high operating costs; the average analysis of the algorithm leads to important geometric features in the graph. The impact of changes in the overall similarity, resulting in a certain deviation in accuracy and stability

[0007] Existing face recognition is not accurate in extracting facial images, which affects the accuracy of face recognition; at the same time, face recognition is inefficient and time-consuming

[0008] In the existing graphic segmentation, the common recognition method of similarity does not match intuitively with the matching of visual resolution, and the algorithm is complex, resulting in a large amount of data processing, high operating costs, and a certain deviation in accuracy and stability.

[0009] The data processing accuracy of the existing technology is poor

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