The invention relates to a handwritten number recognition and incremental type obscure support vector machine method, and can effectively solve the problem of handwritten number accuracy recognition. The technical scheme includes the following steps: collecting images of handwritten numbers, and carrying out binarization processing; segmenting the collected images; formatting a training set with the images of the handwritten numbers to be input and the numbers from zero to nine to be output; formatting an increment function which is mapped to an interval between zero to one; setting lambada to represent an incrementation parameter and a computing complexity parameter of an obscure support vector machine; determining the category of the handwritten numbers according to a classification hyperplane between any two handwritten numbers; examining recognition accuracy on known category handwritten numbers to determine the method of the category of the handwritten numbers; and meeting the requirement of user recognition accuracy and recognizing unknown handwritten numbers. The method is high in recognition accuracy, suitable for practice and recognition of the support vector machine, simple and easy to operate, and is an innovation based on the handwritten number recognition and incremental type obscure support vector machine method.