Download - Bangla Digit Recognition Using NN
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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
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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
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1. Image Preprocessing Image Acquisition
Convert to grayscale image
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1. Image Preprocessing Contt. make the image binary image &check for the
maximum connected component
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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)));
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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
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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
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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
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4. Testing the NN Testing Input:
Testing Output: 1 3 10 4 10 7 6 8 9 5 Testing Result Concatenated Individual Digits:
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Performance : Case 1
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Performance : Case 2
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Performance : Case 3
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Performance : Case 4
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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%
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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
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Thank You Any Questions / Suggestions ?