image processing

1. 1. Introduction
Fig. 1 Image representation of a true-color image in data form
Image Representation
Face detection : A novel approach
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2. 1. Introduction
Image Representation
Face detection : A novel approach
 Types in digital form –
 Binary
 Grayscale
 Truecolor
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3. 1. Introduction
Fig. 2 Binary image
Image Representation
Face detection : A novel approach
Fig. 3 Grayscale image
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4. 1. Introduction
Fig. 4 Truescale image
Image Representation
Face detection : A novel approach
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5. 1. Introduction
Face detection and use
Face detection : A novel approach
 Locating faces in crowd and counting no. of persons
present.
 Detecting faces in poor quality images with insufficient
brightness and contrast.
 Locating faces in search operations in deserted areas.
 Tracking presence of persons in a prohibited area.
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6. 2. Literature Review
Methods of face detection
 Knowledge based method
 Features based method
 Template based method
 Appearance-based method
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7. 2. Literature Review
Methods of face detection
 Knowledge based method
 Features based method
 Template based method
 Appearance-based method
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8. 3. Theoretical Development
Procedure carried out for face detection : -
 Rgb image is converted to grayscale.
 Clustering algorithm is applied to the data sets of pixels in order to
segregate pixels based on their values.
 Color image segmentation is obtained.
 Transformation into binary image.
 Edges are detected using Sobel operator.
 Removing noise from the image.
 Region filling for proper pixel reach-out and appropriation.
 Rejecting non faces pixels by replacing them with black pixels. Only
large group pixels remain.
 Face easily located by placing black square boxes around these pixel
groups.
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9. 4. Experiments
Steps followed in producing face detection are : -
RGB image Rgb image is converted to grayscale.
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10. 4. Experiments
Steps followed in producing face detection are : -
Clustering algorithm is applied to the
data sets of pixels in order to segregate
pixels based on their values.
Segmented image
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11. 4. Experiments
Steps followed in producing face detection are : -
Edges are detected using Sobel operator.
Color image segmentation is obtained.
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12. 4. Experiments
Steps followed in producing face detection are : -
Binary image Applying morphological operations
& noise removal
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13. 4. Experiments
Steps followed in producing face detection are : -
Region filling for proper pixel
reach-out and appropriation.
Rejecting non faces pixels by
replacing them with black pixels.
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14. 4. Experiments
Final result : faces detected inside black square boxes
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15. 4. Experiments
Image 2 tested with the procedure : -
RGB Test image 2 Face detected in Test image 2
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16. 5. Conclusion & Suggestion for Future Work
Experiment Result : -
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