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![BIBLIOGRAPHY
• Gonzalez and Woods, Digital Image Processing. Pearson Education Inc.
• Rudra Pratap, Getting Started With MATLAB, Oxford University.
• http://ivpl.eecs.northwestern.edu/research
• Image processing with Aggelos K. Katsaggelos [M.S., Ph.D. degrees in electrical
engineering from the Georgia Institute of Technology, Atlanta, Georgia].](https://image.slidesharecdn.com/digitalimageprocessingusingmatlabwitharduino1-180907210958/85/Digital-Image-Processing-using-MatLAB-with-Arduino-27-320.jpg)
![BIBLIOGRAPHY
• Gonzalez and Woods, Digital Image Processing. Pearson Education Inc.
• Rudra Pratap, Getting Started With MATLAB, Oxford University.
• http://ivpl.eecs.northwestern.edu/research
• Image processing with Aggelos K. Katsaggelos [M.S., Ph.D. degrees in electrical
engineering from the Georgia Institute of Technology, Atlanta, Georgia].](https://image.slidesharecdn.com/digitalimageprocessingusingmatlabwitharduino1-180907210958/75/Digital-Image-Processing-using-MatLAB-with-Arduino-27-2048.jpg)
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Digital Image Processing using MatLAB with Arduino
- 1. DIGITAL IMAGE PROCESSINGUSING MATLAB WITH ARDUINO PREPARED BY SHIVANG RANA (14BEE099) RAJ PATEL (14BEE091) GUIDED BY PROF. MAYUR GOJIYA
- 2. OVERVIEW OF THESESSION • 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 • Block Diagram of Comparing to Two Images
- 3. WHAT IS ADIGITAL IMAGE? • Digital image can be defined as set of digital values arranged in 2-dimensional manner. • Sampling of image (A) 1 sample/point (B) 3 sample/point (C) Multi sample/point
- 4.
- 5. HOW PROCESSING ISDONE ON DIGITAL IMAGE • Process on digital image focus on 2 major parts (A) Enhancement of pictorial information for human understanding (B) Processing of image for storing, transmitting and receiving data. IR vision image of PCB Picture taken & enhanced by drone
- 6. CLASSIFICATION OF IMAGES •Reflection Images - Information primarily about object surfaces - Optical imaging, radar, sonar, laser • Emission Images - Information primarily to the internal object - Thermal, Infrared, MRI (Magnetic Resonance Interference) • Absorption Images - X-rays, Transmission microscopy, Types of sonic images
- 7. BLOCK DIAGRAM OFDIGITAL IMAGE PROCESSING Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition External world
- 8. IMAGE RESTORATION Image after enhance Degradation function + Noise function Restoration filter Restore dImage Image Restoration is the operation of taking a corrupt/noisy image and estimating the clean, original image.
- 9. MORPHOLOGICAL PROCESSING • Morphologyis a broad set of image processing operations that process images based on shapes. Morphological operations apply a structuring element to an input image, creating an output image of the same size. In a morphological operation, the value of each pixel in the output image is based on a comparison of the corresponding pixel in the input image with its neighbors.
- 10. SEGMENTATION • It isa process of partitioning a digital image into multiple segments (sets of pixels). • The goal of segmentation is to simplify or change the representation of an image into something that is more meaningful and easier to analyze. Source image Segmented image
- 11. OBJECT RECOGNITION • Objectrecognition is a process for identifying a specific object in a digital image or video. Object recognition algorithms rely on matching, learning, or pattern recognition algorithms using appearance-based or feature-based techniques.
- 12. QUANTIZATION 8 bit perpixel 4 bit per pixel 2 bit per pixel
- 13. STEREO IMAGE ANDDISPARITY
- 14.
- 15. APPLICATIONS OF IMAGEPROCESSING - Face Recognition - For Quality Assurance - Space exploration and Astronomy - Medical Applications to detect tumour - For Image Restoration processes - Security System Applications - Document Verification - Video and Film Effects - Neural Network - Agricultural sorting - Geographical image processing
- 16. HOW ACTUALLY IMAGEPROCESSING WORKS? • Low level process: Noise removal & Image Sharpening - I/p : Image O/p : Image • Mid Level process: Object Recognition & Segmentation - I/p : Image O/p : Attributes • High Level process: Scene Understanding & Autonomous Navigation - I/p : Attributes O/p : Understanding
- 17. QUALITY CHECK FORAPPLE FRUIT ALGORITHM
- 18. Fruit Quality CheckerBlock Diagram
- 19. 1: Bright Light 2:Bright Light 3: CMOS Camera 4: Object (Apple) Processing Flow for the Quality System
- 20. 1) COLOUR DETECTION •In this process of fruit colour detected according to RGB values, here fruits are sorted according to colour and size. • RGB values for every colour is different combination. • Algorithm: - Take small areas colour values of RGB and take all their mean. And store in a RGB (3 coordinate) variable. - Compare the value with threshold i.e if G > then threshold => Green coloured
- 21. 2) EDGE DETECTION •Once colour is detected, size is needed to be found out. • Edge Extraction is key factor in this kind of fruit sorting algorithm • First Grey image is found. And then Canny method is the best to find out the edge of any object.
- 22. FRUIT SIZE GRADING •We need to keep some standard values for apple size through which we can compare the test apple with best apple.
- 26.
- 27. BIBLIOGRAPHY • Gonzalez andWoods, Digital Image Processing. Pearson Education Inc. • Rudra Pratap, Getting Started With MATLAB, Oxford University. • http://ivpl.eecs.northwestern.edu/research • Image processing with Aggelos K. Katsaggelos [M.S., Ph.D. degrees in electrical engineering from the Georgia Institute of Technology, Atlanta, Georgia].