Optical identification method and optical identification system

An optical identification method, for sensing a physiological feature, including:

• projecting light to a physiological portion for generating reflection light from the physiological portion;
• receiving the reflection light by a sensor unit, to accordingly generate at least one image;
• generating slant pattern information according to the at least one image;
• transforming the slant pattern information into at least one pattern identification matrix;
• and
• determining the physiological feature according to the pattern identification matrix;
• wherein the sensor unit includes a horizontal direction and a vertical direction, and the slant pattern information includes a positive slope pattern and/or a negative slope pattern, wherein the positive slope pattern includes a positive slope between zero and positive infinity with reference to the horizontal direction and the vertical direction, and the negative slope pattern includes a negative slope between zero and negative infinity with reference to the horizontal direction and the vertical direction;
• wherein the at least one image includes a plurality of images, and the at least one pattern identification matrix includes a plurality of pattern identification matrices sequentially obtained according to the images;
• wherein when the physiological portion includes at least a part of a finger, and the physiological feature is a finger motion trajectory, the step of determining the physiological feature according to the pattern identification matrix includes:
• determining the finger motion trajectory according to the pattern identification matrices;
• wherein each of the images includes a pixel matrix, and the step of generating the slant pattern information according to the images further includes:
• obtaining a sample matrix in the pixel matrix, wherein the sample matrix includes a central pixel, and a plurality of pixels surrounding the central pixel, wherein the pixels surrounding the central pixel include an upper right corner pixel, a lower right corner pixel, an upper left corner pixel, and a lower left corner pixel with reference to the horizontal direction and the vertical direction;
• transforming the sample matrix into a characteristic matrix, wherein the characteristic matrix includes elements arranged by a plurality of horizontal element rows in the horizontal direction and the same plurality of vertical element columns in the vertical direction, wherein a sum of digital values of all the elements in the same horizontal element row equals zero, and a sum of digital values of all the elements in the same vertical element column equals zero;
• generating the slant pattern information corresponding to each of the sample matrices, by a convolution operation between each of the characteristic matrices and a mask matrix;
• and transforming a resulted convolution value corresponding to each of the sample matrices into 1-bit data as the slant pattern information.