1. An image recognizing method, recognizing at least one testing image according to a plurality of classes, wherein each of the classes comprises a plurality of sample images, the image recognizing method comprising: generating an average image of each of the classes according to the sample images; generating a feature enhancement mask according to differences between the average images of the classes; enhancing the sample images of each of the classes by using the feature enhancement mask to generate a plurality of enhanced sample images corresponding to the class; training a classifier according to the enhanced sample images corresponding to each of the classes; enhancing the at least one testing image by using the feature enhancement mask to generate at least one enhanced testing image; classifying the at least one enhanced testing image into one of the classes by using the classifier; and recognizing that the at least one testing image belongs to the one of the classes, wherein each of the sample images has a plurality of pixels arranged into an array, each of the pixels is corresponding to a pixel value, and the average image of each of the classes has a plurality of average pixel values corresponding to the pixels of the sample images, wherein the average pixel value in an i th column and a j th row of the average image of an m th class is obtained by dividing a sum of the pixel values corresponding to the pixels in the i th columns and the j th rows of the sample images of the m th class by the number of the sample images of the m th class, wherein the feature enhancement mask has a plurality of feature enhancement values arranged into the array, and the feature enhancement values are obtained according to a plurality of absolute differences between the average pixel values of the average images of the classes, wherein a number of the classes is 2, wherein the absolute differences are arranged into the array, and a value in an i th column and a j th row of the absolute difference among the absolute differences is equal to an absolute value of a difference between the average pixel value in the i th column and the j th row of the average image of a 1 st class among classes and the average pixel value in the i th column and the j th row of the average image of a 2 nd class among classes, wherein the feature enhancement value in an i th column and a j th row of the feature enhancement mask is obtained by dividing the value in the i th column and the j th row of the absolute difference among the absolute differences by a maximum absolute difference among the absolute differences.