Face recognition device and method
A face recognition and face image technology, applied in the field of face recognition, can solve the problems of identification errors, unequal quality of face image data, and low recognition accuracy, and achieve accurate image feature extraction, improve image quality, and improve recognition. The effect of precision
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Embodiment 1
[0046] On the one hand, the present invention provides a face recognition device, such as figure 1 and figure 2 As shown, it includes a face acquisition device for collecting face images and an image processing system for processing the collected face images. The image processing system includes an image acquisition module, a sample training module and a face recognition module. The collection module is used to collect images of faces, the sample training module is used to process the collected face images and extract characteristic information, the face recognition module is used to match the collected face images with extracted feature information, and Complete face recognition.
[0047] In this embodiment, the face acquisition device is designed based on the image sensor CCD. The image sensor CCD is also called a charge coupling element, which is a semiconductor device that can convert optical images into digital signals, and convert the acquired user image signals into ...
Embodiment 2
[0051] As the second embodiment of the present invention, in order to facilitate the collection of images of human faces, the inventors improved the image collection module, as a preferred embodiment, such as Figure 3-Figure 4 As shown, the image acquisition module includes an image import module, a geometric processing module, a geometric normalization module, a grayscale processing module, a histogram equalization module, a weighted value filtering module and a feature extraction module. The image import module is used to convert the collected The face image is imported into the image processing system, the geometry processing module is used to locate the imported face image, and the geometry normalization module is used to rotate and cut the positioned face image to form a unified standard and grayscale The processing module is used to convert the color image into a grayscale image to speed up the processing. The histogram equalization module is used to adjust the grayscale...
Embodiment 3
[0073] As the third embodiment of the present invention, in order to facilitate the processing of the collected face images and extract the characteristic information, the inventors improved the image acquisition module, as a preferred embodiment, such as Figure 5-Figure 6 As shown, the sample training module includes a sample collection module, a sample description file module, a vec file creation module, and a training image module. The sample collection module uses the harr feature of the sample for classifier training to obtain a cascaded boosted classifier, and establishes a sample The description file module is used to create a pos.txt file, and note the number of times and names of pictures. The vec file module uses the opencv_createsamples.exe built-in program to create a vec file. The training image module is used to use opencv_haartraining.exe for image training and collection. The sample module includes a positive sample collection module and a negative sample colle...
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