bangla digit recognition using nn

Project Presentation ofBangla Digit Recognition using NN

Project Members:

Mohammad Nazmul Haque

Roni Shikder

Susmita Baidya

Ehsan Uddin Ahmed

Submitted to:Prof. Syed Akhter Hossain, Ph.DDaffodil International University

Presentation Outline1. Image Preprocessing

Image Acquisition Convert to Gray Scale Convert to Binary Image Identify maximum connected component Crop Individual character & make raw data Resize character into 5x7 ,applying fuzzy

technique

2. Create Neural Network3. Training the Network4. Testing The Network5. Performance Evaluation

1. Image Preprocessing Image Acquisition

Convert to grayscale image

1. Image Preprocessing Contt. make the image binary image &check for the

maximum connected component

1. Image Preprocessing Contt..

Crop individual characters & make raw data

sub-images have been resize to 50 by 70

bw_7050=imresize(bw2,[70,50]);

finding the average value in each 10 by 10 blocks

Atemp=sum(bw_7050((cnt*10-9:cnt*10),(cnt2*10-9:cnt2*10)));

1. Image Preprocessing Contt..

image can be down to 5 by 7 matrices, with fuzzy value

for cnt=1:7

for cnt2=1:5

Atemp=sum(bw_7050((cnt*10-9:cnt*10),(cnt2*10-9:cnt2*10)));

lett((cnt-1)*5+cnt2)=sum(Atemp);

end

end Resize Digit by 5x7 by average value

2. Create the NN Classification by simple FF-BP-NN The number of features, which is 5 by 7 = 35

Performance Goal : 0.01 Momentum constant : 0.95 Epochs : 5000

3 . Training the Network

Training Output Training Performance

TRAINGDX, Epoch 0/5000, SSE 100.468/0.1, Gradient 51.6634/1e-006TRAINGDX, Epoch 20/5000, SSE 39.1175/0.1, Gradient 0.755705/1e-006TRAINGDX, Epoch 40/5000, SSE 39.7742/0.1, Gradient 0.247939/1e-006TRAINGDX, Epoch 60/5000, SSE 39.8531/0.1, Gradient 0.1739/1e-006TRAINGDX, Epoch 80/5000, SSE 39.8688/0.1, Gradient 0.159411/1e-006TRAINGDX, Epoch 100/5000, SSE 39.8692/0.1, Gradient 0.160278/1e-006TRAINGDX, Epoch 120/5000, SSE 39.8604/0.1, Gradient 0.171435/1e-006TRAINGDX, Epoch 140/5000, SSE 39.827/0.1, Gradient 0.211754/1e-006TRAINGDX, Epoch 160/5000, SSE 39.628/0.1, Gradient 0.438358/1e-006TRAINGDX, Epoch 180/5000, SSE 34.2116/0.1, Gradient 2.91705/1e-006TRAINGDX, Epoch 200/5000, SSE 11.2205/0.1, Gradient 2.92171/1e-006TRAINGDX, Epoch 219/5000, SSE 0.0846207/0.1, Gradient 0.160478/1e-006TRAINGDX, Performance goal met

0 20 40 60 80 100 120 140 160 180 20010

-2

10-1

100

101

102

103

219 Epochs

Tra

inin

g-B

lue

Goa

l-Bla

ck

Performance is 0.0846207, Goal is 0.1

4. Testing the NN Testing Input:

Testing Output: 1 3 10 4 10 7 6 8 9 5 Testing Result Concatenated Individual Digits:

Performance : Case 1

Performance SummaryParticulars Result

No of Training Digit 160

No of Testing Digit 40

No of Miss-Classification 2

Miss-Classified Digits ১, ৩ as ৯ , ০Performance (Success Rate) 95%

Future Scope Create NN based Bangla Number recognition

System Car’s Bangla Number Plate Recognition

System Road Speed Limit recognition system for

Bangla Road Sign

Thank You Any Questions / Suggestions ?

bangla digit recognition using nn

Documents