linecode / handwritten-digits-recognition

Automatically recognize handwritten digits from photos. Handwritten digits recognition by CNN and SVM.

Handwritten Digits Recognition

Automatically recognize handwritten digits from photos. Handwritten digits recognition by convolutional neural network and Support Vector Machine. Implement with Python, numpy and OpenCV.

For more details about the theory, implementation and results, please read my post (in chinese). Any feedback is welcomed!

Method

We can do this in three steps. Firstly, segment strings of digits into digits one by one. Then train models/classifiers by CNN with TensorFlow and SVM with scikit-learn framework. Lastly, test and get results.

To segment digit strings, firstly we need to detect and crop paper sheet in photo (please refer to A4-paper-sheet-detection-and-cropping). Secondly process image with binary conversion. Thirdly judge the handwritten direction to detect digit strings. Lastly segment digits in a digit string.

Results

Dividing MNIST dataset into training and testing set, the accuracy of SVM can be 0.9852 and the accuracy of CNN can be 0.992. When testing on my own handwritten digits dataset, the accuracy is lower (~0.7 for SVM and ~0.9 for CNN).

Data Number	0	1	3	4	5+6+7	average
SVM accuracy	9 / 14 = 0.642857	8 / 17 = 0.470588	46 / 60 = 0.766667	28 / 39 = 0.717949	59 / 73 = 0.808219	150 / 203 = 0.738916
CNN accuracy	12 / 14 = 0.857143	10 / 17 = 0.588235	48 / 60 = 0.800000	32 / 39 = 0.820513	73 / 73 = 1.000000	175 / 203 = 0.862068