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Digit recognition based on
using template matching
Presented By:
Anik Deb Nath
ID: 1803510201673
Dept. of CSE, PUC
Contents
Motivation
Objective
01
02
Applications
03
Methodology
04
Processing Example
05
Conclusion
06
Appendix
07
g
(b)
01 Objectives
• Recognition digit for given image using template matching .
Figure for Processing Example : (a) Template & candidate image (b)
Template matching algoithm (c) Recognize digit image
Matching similarity by NCC
(a)
(c)
02 Motivation
Traditional methods often struggle to handle various fonts, styles, and
handwriting.
01
02
03 Ensuring accurate digit extraction and interpretation,
To minimize human error, inefficiencies and inaccuracies.
Applications
• Numeric entries in forms filled up by hand
• Processing bank check amounts
• Room Number
03
Methodology
04
Input image normalize by size
Convert images to grayscale.
Convert to binary using Otsu's thresholds
Complement Binary Images
Calculate Candidate Mean
NCC Loop
Find Best Match
Visualize result by rectangle box
Template
Candidate(digit)
Process Example - 1
05
Fig 1: Read RGB image and convert
to grayscale image
Fig 2: Convert gray to binary and
take the complement of binary
image
Fig 3: Display the current template,
candidate and best match
Process Example -2
06
Fig 1: Read RGB image and convert
to grayscale image
Fig 2: Convert gray to binary and
take the complement of binary
image
Fig 3: Display the current template,
candidate and best match
Conclusion
07
In conclusion, the code demonstrates a basic implementation of digit recognition using the NCC
technique.
Merits of NCC:
• Easy to understand and implement.
• Effective for finding patterns.
• Clear interpretation of results.
• Doesn't need extensive training.
Demerits of NCC:
• Can be slow for large images.
• Only good for exact or near-exact matches.
• Affected by similar patterns in the background.
• Challenging to set accurate thresholds.
• Struggles with noise, and variations.
Appendix
08
Appendix
09
Appendix
10
Appendix
11
Thank You

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Digit-recognition-based-on-using-template-matching-Presentation.pdf

  • 1. Digit recognition based on using template matching Presented By: Anik Deb Nath ID: 1803510201673 Dept. of CSE, PUC
  • 3. g (b) 01 Objectives • Recognition digit for given image using template matching . Figure for Processing Example : (a) Template & candidate image (b) Template matching algoithm (c) Recognize digit image Matching similarity by NCC (a) (c)
  • 4. 02 Motivation Traditional methods often struggle to handle various fonts, styles, and handwriting. 01 02 03 Ensuring accurate digit extraction and interpretation, To minimize human error, inefficiencies and inaccuracies.
  • 5. Applications • Numeric entries in forms filled up by hand • Processing bank check amounts • Room Number 03
  • 6. Methodology 04 Input image normalize by size Convert images to grayscale. Convert to binary using Otsu's thresholds Complement Binary Images Calculate Candidate Mean NCC Loop Find Best Match Visualize result by rectangle box Template Candidate(digit)
  • 7. Process Example - 1 05 Fig 1: Read RGB image and convert to grayscale image Fig 2: Convert gray to binary and take the complement of binary image Fig 3: Display the current template, candidate and best match
  • 8. Process Example -2 06 Fig 1: Read RGB image and convert to grayscale image Fig 2: Convert gray to binary and take the complement of binary image Fig 3: Display the current template, candidate and best match
  • 9. Conclusion 07 In conclusion, the code demonstrates a basic implementation of digit recognition using the NCC technique. Merits of NCC: • Easy to understand and implement. • Effective for finding patterns. • Clear interpretation of results. • Doesn't need extensive training. Demerits of NCC: • Can be slow for large images. • Only good for exact or near-exact matches. • Affected by similar patterns in the background. • Challenging to set accurate thresholds. • Struggles with noise, and variations.