Blob detection techniques explained in simple way

1. BLOB DETECTION
Raja Raheel
Raja Osama
Sikander

2. WHAT IS BLOB DETECTION?
 In computer vision blob detection is method use to detect region that
differ in properties, such as brightness or color or shape.
 A blob is region of image in which some properties are constant.

3. WHY WE USE BLOB DETECTION?
 Blob detection is used to obtain region of interest from an digital
image.
 Sometime we use blob detection for texture analysis and texture
recognition.
 We also use blob detection for object recognition.
 Blob detection is usually done after color detection and noise reduction
to finally find the required object from the image.

4. BLOB DETECTION TECHNIQUES
 Laplacian Filter
 Object detection technique
 Feature Extraction
 Image merging & mosaicing

5. LAPLACIAN FILTER
 Laplacian filter is one of techniques of blob detection.
 In this technique we simply apply laplacian mask on an image
 As result of which we get output/processed image as binary image
having region of interest/blobs as white and other object and
background as black.

6. LAPLACIAN FILTER

7. LAPLACIAN FILTER

8. OBJECT DETECTION
 As name indicates that object detection is technique to detect object
from an image.
 Object detection is process of finding objects of real world such as
faces, cars, bicycle, buildings etc. depend upon what you are interested
to detect.
 Lets detect an object from an image depending upon one its property
that object should be red in color.

9. EXAMPLE 1

10. EXAMPLE 2

11. OBJECT DETECTION

12. OBJECT DETECTION

13. FEATURE EXTRACTION
 Feature extraction is one of technique of blob detection.
 We extract feature from an digital image.
 After extraction we do further processing on image depend on our
requirement.

14. FEATURE EXTRACTION

15. EXTRACT FEATURES
Step 1: extract features Step
2: match features

16. FEATURE EXTRACTION
 Step 1: extract features
 Step 2: match features
 Step 3: align images