Introduction of image processing
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It is the basic introduction of how the images will be captured and converted form analog to digital format by using sampling and quantization process and further algorithms will be apply on the digitized image.
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The document discusses a computer vision workshop that covered topics including what a digital image is, what digital image processing is, examples of digital image processing, and key stages in digital image processing. It defines a digital image as a finite set of pixels representing properties like gray levels or color. Digital image processing focuses on improving images for interpretation and processing images for storage, transmission and machine perception. Examples covered include image enhancement, medical imaging, geographic information systems, law enforcement, and object segmentation. Key stages discussed include image acquisition, restoration, enhancement, representation and description, segmentation, and compression.
imp.pptx
This document discusses the fundamental steps in digital image processing. It describes 10 main steps: 1) image acquisition, 2) enhancement, 3) restoration, 4) color processing, 5) wavelets, 6) compression, 7) morphological processing, 8) segmentation, 9) representation and description, and 10) recognition and interpretation. The goal of these steps is generally to improve images for human interpretation or machine perception through techniques like filtering, segmentation, and feature extraction.
Image processing presentation
This document provides an overview of image processing. It defines analog and digital images and discusses common file formats like JPEG, PNG, BMP and GIF. Image processing involves performing operations on images to extract useful information or enhance the image. There are three levels of image processing - low level focuses on preprocessing, middle level extracts attributes, and high level analyzes attributes. Applications include digitization, enhancement, restoration, segmentation, recognition and more across fields like medicine, law enforcement, human-computer interfaces and steganography. In conclusion, image processing has broad applications in science and technology due to the growing importance of scientific visualization.
Digital image processing & computer graphics
Digital Image Processing & Computer Graphics document discusses several topics related to digital image processing including:
1. Digital image processing involves manipulating digital images using computer programs. It includes operations like geometric transformations, image refinement to remove noise, color adjustments, and combining multiple images.
2. Computer graphics is focused on constructing images, while digital image processing is focused on manipulating existing images.
3. Common digital image processing techniques discussed include image enhancement to improve image quality, image restoration to remove degradation, image segmentation to separate objects, image resizing, compression, and feature extraction.
4. Image filtering is used to reduce noise in images using techniques like convolution with filters that target different image frequency ranges like low-pass and
Digital Image Processing
A very brief introduction to What is Digital Image Processing. Components of a Digital Image Processing System and A Machine Vision System.
Unit 1 DIP Fundamentals - Presentation Notes.pdf
This document discusses the fundamentals of digital image processing. It begins by defining a digital image and explaining that digital image processing involves processing digital images using a computer. It then outlines 12 fundamental steps in digital image processing, including image acquisition, enhancement, restoration, compression, and pattern classification. Finally, it describes the typical components of an image processing system, including sensors, digitizers, computers, software, storage, and specialized hardware.
Digital image processing
Digital image processing involves performing operations on digital images using computer algorithms. It has several functional categories including image restoration to remove noise and distortions, enhancement to modify the visual impact, and information extraction to analyze images. The main steps are acquisition, enhancement, restoration, color processing, compression, segmentation, and filtering using techniques like pixelization, principal components analysis, and neural networks. It has applications in medical imaging, film, transmission, sensing, and robotics. The advantages are noise removal, flexibility in format and manipulation, and easy storage and retrieval. The disadvantages can include high initial costs and potential data loss if storage devices fail.
1 dip introduction
The document discusses the objectives and outcomes of a course on digital image processing. The course aims to introduce students to fundamental image processing techniques including image enhancement, restoration, compression and segmentation. It will also cover color image processing and different methods to represent color images. The syllabus outlines topics like digital image basics, enhancement, restoration, compression, color processing and segmentation that will be covered in the course.
Digital Image Processing using MatLAB with Arduino
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Image proccessing and its applications.
this presentation based on the image processing and its one of the process that is image compression.
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Introduction of image processing
- 1. Introduction of Digital Image Processing
- 2. What is an image?
- 3. Basic elements of an image processing • Image Acquisition (camera) • Image storage (Frame grabber card) • Image processing (Algorithms) • Display (monitor/VGC) • Transmission (If required) 3
- 4. Image types: 1. Monochrome images (Binary image-single bit) 2. Grey scale images (8bits-3 samples per point) 3. Color image (24-bit-8 samples per point)` 4
- 5. Image format • BMP • TIFF • GIF • JPEG 5
- 6. Sampling and Quantisation To digitize the analog images. Digitization= Sampling +Quantization Sampling: Convolution in time domain is multiplication in frequency domain and vice versa. 6
- 7. A digital image is a representation of a two-dimensional image as a finite set of digital values, called picture elements or pixels. F(x , y)= 7 1 pixel Pixel values typically represent gray levels, colors, heights, etc. Digitization implies that a digital image is an approximation of a real scene
- 8. The way from Image processing to Computer vision is from three levels processes Image Processing Computer Graphics Computer Vision Level 1 Noise removals Level 2 Object Recognition & Segmentation Level 3 Scene understanding & automated Navigation 8
- 9. Digital Image Processing System 9 Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression
- 10. 10 Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression Digital Image Processing System : Image Enhancement
- 11. Digital Image Processing System : Image Restoration 11 Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression
- 12. Digital Image Processing System : Morphological Processing 12 Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression Image Acquisition
- 13. Digital Image Processing System : Segmentation 13 Image Restoration Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression Morphological Processing Segmentation Image Acquisition Segmentation
- 14. Digital Image Processing System : Object Recognition 14 Image Acquisition Image Restoration Morphological Processing Segmentation Image Enhancement Problem Domain Colour Image Processing Image Compression Representation & Description Object Recognition
- 15. Digital Image Processing System : Representation & Description 15 Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression
- 16. Digital Image Processing System : Image Compression 16 Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression
- 17. Digital Image Processing System : Colour Image Processing 17 Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression
- 18. Applications of Image processing 1. Biometrics 2. Medical 3. Space 18
- 19. Biometric System • Biometrics comprises methods for uniquely recognizing humans based upon one or more intrinsic physical or behavioral traits. • Physiological are related to the shape of the body. • Behavioral are related to the behaviour of a person. Examples like Gait, Voice, Signature and Key Stroke. 19
- 20. Physiological & Behavioral Biometric Traits 20
- 21. 21
- 22. Thank you.. May 26, 2016 Sample footer 22