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Digital Image Processing & Machine Vision – An Introduction

In this introduction to digital image processing, we explore the concept of digital images, their processing tasks, various types, and applications. We also discuss the difficulties faced in image processing.

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Digital Image Processing & Machine Vision – An Introduction

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  1. Digital Image Processing & Machine Vision – An Introduction Prepared by: - Mr. T.R.Shah, Lect., ME/MC Dept., U. V. Patel College of Engineering. Ganpat Vidyanagar.

  2. Today's topics • Introduction to an image. • Why digital image?? • What is digital image?? • What is digital image processing?? • Digital image processing task. • Applications. • Types of digital images. • Difficulties in image processing. • Study on your own.

  3. Introduction to image • An natural image captured with a camera, telescope, microscope or other type of optical instrument displays a continuously varying array of shades and color tones. This is known as continuous tone image or analog image. • An image provides information.

  4. Why DIGITAL IMAGE?? • Storage of an analog image !!! • Processing an analog image !!! Answer is impossible to store and difficult to Process the image.

  5. What is Digital image?? • A digital image differs from an photo in that x,y and f(x,y) values are discrete.

  6. What is Digital Image Processing?? • Image processing involves changing the nature of an image in order to either 1) improve pictorial information for human interpretations, or 2) render it more suitable for autonomous machine perception 3) reducing image size on disk

  7. An Image Processing Task Preprocessing (Enhancement & Restoration) Representation & Description Segmentation Knowledge Base Problem Domain Image Acquisition Recognition & Interpretation Result *Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Addison-Wesley, 1992

  8. Applications • Lane tracking & Guidance of an autonomous vehicle:- N.B.:- Project submitted by Sagar Shukla & his group(2009).

  9. Applications – block diagramLane tracking & Guidance of an autonomous vehicle Image Capture Image Processing And Analysis Lane Identification Steering Control Control Circuit

  10. ApplicationsReal model of Manipulator • Object detection in Pick & Place Robotic Manipulator:- Camera Stepper Motor Sliders Object N.B.:- Project submitted by Anant Jain & his group (2009).

  11. Applications- CAD modelObject detection in Pick & Place Robotic Manipulator

  12. ApplicationObject detection in Pick & Place Robotic Manipulator – block diagram Image Processing Interfacing Image Acquisition M/C CONTROLLER Sensors (Feedback) Manipulator

  13. Applications • Object Follower : - N.B.:- Project submitted by Parth Chopra & Karan Dave(2010).

  14. Object Follower Image acquisition Noise Removal Edge detection Block Diagram Morphological operation Motion control Area and C.G Measurement Shape Detection

  15. Applications • Automatic Character Recognition :- N.B.:- Project submitted by Tarun Patel & his group (2010).on “Number Plate Recognition and Parking”

  16. Block diagram for OCR Convert RGB to Gray image Convert to binary image via threshoding and invert image Image acquisition Apply morphological operation for number plate recognition Convert number in text or excel OCR Algorithm Parking

  17. Applications • Image Inpainting: - N.B.:- Dissertation work done by Prof. Priyank Thakkar (CE Dept., UVPCE).

  18. Types of digital Images • Binary image • Gray scale image, • True color image or RGB image, • Indexed image.

  19. Difficulty in digital image processing • Image size • Gray scale image of 512 X 512 requires = 512 X 512 X 8 = 2097152 bits. = 2MB • 3D image perception

  20. Assignment • Think about a block of blue color. Notice the color of an object when seen under white lighting. • Think about a block of blue color. Notice the color of an object when seen under yellow lighting. • Take a block of gray color and put it on white back ground. Note down the brightness of object. Now, take the same block & put it on black background. Notice the difference for two cases. • Create picture using paint. Save it in jpg format. Save as the same picture using 24 bit true color bmp format. Now, check the property of two image and comment on size of same picture but saved in different formats • Use your mobile phone low resolution camera & get image of dark sky at night. Keep night mode on. Capture an image , get soft copy and conclude about original scene & picture. (Mark color other than black.)

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