![ALGORITHM FOR PIXEL DETECTION TECHNIQUE:
Choosing a
particular pixel
Value e.g
(R,G,B):(255,0,0)
Saving pixel value
in an 3-Array e.g
Array_ref
=(255,0,0)
Capturing a
whole data of
array’s from video
image obtained
(30fps)
Comparing the array
obtained for ith pixel (
pix(i)_Array ) with Array_ref:
Comp= [pix(i)_Array] -
[Array_ref]
If Comp==0;
pixel is detected
and put a circle
there at ith pixel
If Comp=!0;
pixel is not
detected and i++](https://image.slidesharecdn.com/imageprocessing-180907211651/85/Image-Processing-TARUS-a-FARMBOT-9-320.jpg)
![ALGORITHM FOR MOTION DETECTION:
Capture a image of video
(30fps) at t= ith sec:
Make a array of pixel values
of image: Array_pix(x)(y)(i)
x & y are 2D coordinates
Initialize: each
pix_value(x)(y)=blac
k
Capture a image of video
(30fps) at t= (i+1)th sec:
Make a array of pixel
values of
image:Array_pix(x)(y)(i+1)
Comp=[Array_pix(x)(y)(i+1)
- Array_pix(x)(y)(i)]
If Comp==0;
No motion
detected
pix_value(x)(y)=blac
k
If Comp=!0;
New motion detected
pix_value(x)(y)=white
If pix_value(x)(y)==pix_value(x+i)(y+j)==white;
Motion is detected in (i)(j) direction
Put a track ball in (i)(j) direction](https://image.slidesharecdn.com/imageprocessing-180907211651/85/Image-Processing-TARUS-a-FARMBOT-10-320.jpg)
Image Processing TARUS: a FARMBOT
- 1. DIGITAL IMAGE PROCESSING Using Arduino & Matlab REVIEW-II Raj Patel (14bee091) Rana Shivang (14bee099) Guided by Prof. Mayur Gojiya
- 2. RECAP OF PREVIOUS REVIEW-I ❖ What is digital image? ❖ How processing is done with digital image? ❖ Classification of Image ❖ Block diagram of DIP ❖ Quality Workforce Algorithm for Fruit Sorter ❖ Block Diagram of Face Detection using Spyder ❖ Block Diagram of Comparing to Two Images
- 3. INDEX - Block diagram of Robot functioning. - Hardware required to make robot. - Programming of image processing in MATLAB. (simulation) - Implementation of control circuit in ARDUINO. (simulation) - Development of “TAURUS: v1.0”: a farmbot. - Hardware for dual axis Camera focus system. (video) - Programming in the software: Processing. - Feature Extraction for a Object: Pixel Detection & Motion Detection - Conclusion
- 4. BLOCK DIAGRAM OF ROBOT FUNCTIONING
- 5. HARDWARE REQUIRED 1. Arduino uno 2. Intex 1.0 MP camera 3. L293D driver IC 4. 12V 1.3 Ah battery 5. 12V DC motor 6. Wheels 7. Connecting Pins
- 6. MATLAB PROCESSING & BOT WORKING
- 7. PROCESSING SOFTWARE FOR IMAGE PROCESSING Capabilities: - Capturing image in real time or processed time - Feature extraction from image - Recording real time video with any device - Video processing features
- 8. PROCESSING METHODS IMPLEMENTED 1) Pixel Detection Algorithm 2) Average Pixel Detection method 3) Motion Detection Method
- 9. ALGORITHM FOR PIXEL DETECTION TECHNIQUE: Choosing a particular pixel Value e.g (R,G,B):(255,0,0) Saving pixel value in an 3-Array e.g Array_ref =(255,0,0) Capturing a whole data of array’s from video image obtained (30fps) Comparing the array obtained for ith pixel ( pix(i)_Array ) with Array_ref: Comp= [pix(i)_Array] - [Array_ref] If Comp==0; pixel is detected and put a circle there at ith pixel If Comp=!0; pixel is not detected and i++
- 10. ALGORITHM FOR MOTION DETECTION: Capture a image of video (30fps) at t= ith sec: Make a array of pixel values of image: Array_pix(x)(y)(i) x & y are 2D coordinates Initialize: each pix_value(x)(y)=blac k Capture a image of video (30fps) at t= (i+1)th sec: Make a array of pixel values of image:Array_pix(x)(y)(i+1) Comp=[Array_pix(x)(y)(i+1) - Array_pix(x)(y)(i)] If Comp==0; No motion detected pix_value(x)(y)=blac k If Comp=!0; New motion detected pix_value(x)(y)=white If pix_value(x)(y)==pix_value(x+i)(y+j)==white; Motion is detected in (i)(j) direction Put a track ball in (i)(j) direction
- 11. PROTOTYPE TAURUS
- 12. PRECAP OF REVIEW-III - Implementing Blob detection for any fruit and tagging them - Deterioration factor detection for any low hanging fruits - Two axis “Tarus-bot v.2” with metallic framework - Tracking in any direction. - Once images are captured then segmenting fruit image and sending them for feature extraction.
- 13. CONCLUSION