The document provides an introduction to image processing, computer vision, and robot vision. It defines image processing as the process of transforming, encoding, and transmitting an image. Computer vision uses computational tools to understand images and derive human-like descriptions. Robot vision allows machines to see their environment and make automated decisions and actions. The document outlines common applications of image processing in medical, technology, communications, gaming, and photography fields. It also describes the digital image acquisition process.
Spandana image processing and compression techniques (7840228)indianspandana
This document discusses image processing and compression techniques. It begins by stating the objectives of image processing as sharpening images, minimizing degradation, and reducing the amount of memory needed to store images through compression. It then provides introductions and definitions related to digital image processing. The key stages of digital image processing are described as image acquisition, enhancement, restoration, morphological processing, segmentation, object recognition, representation and description, color image processing, and compression. Image compression aims to reduce the amount of data required to represent a digital image by removing redundant data. The goals and flow of image compression are explained. Finally, different compression techniques such as lossless compression using run-length encoding and lossy compression are outlined.
The document describes the Colour Imaging Lab at the University of Granada in Spain. The lab conducts research in areas related to color vision, color images, color constancy, and using RGB cameras to recover spectral information. It has permanent staff and PhD students. It has published papers in international journals and conferences and worked on projects funded by the Spanish and Andalusian governments and private companies. The lab has various instruments including tunable liquid crystal filters, cameras, spectroradiometers, and a 3D scanner. It also teaches courses and hosts international students and thesis students.
Digital image processing focuses on improving images for human interpretation and machine perception. It involves key stages like acquisition, enhancement, restoration, morphological processing, segmentation, and representation. Applications include medical imaging, industrial inspection, law enforcement, and human-computer interfaces. While digital images allow for faster and more efficient processing than analog images, limitations include reduced quality if enlarged beyond a certain file size.
This document provides an overview of visual object recognition. It begins with an introduction explaining why object recognition is a challenging problem and discusses the importance of recognizing objects from different viewpoints, scales, textures, etc. It then describes how recognition can be achieved using local image features rather than analyzing the whole object. The document focuses on the Scale Invariant Feature Transform (SIFT) approach, outlining the key stages of detecting local features, generating invariant representations of those features, and verifying matches between images based on geometric configuration. Overall, the summary provides a high-level view of object recognition techniques with a focus on the seminal SIFT method.
This document summarizes a research paper that proposes a method for converting images and video into portraits and animations using RGB color segmentation. The method involves several steps: edge detection using Sobel operator, blurring the image with Gaussian blur to reduce noise, color segmentation by comparing RGB pixel values to a threshold, and region filling to convert the image into a portrait. The overall goal is to automatically convert still images and video into animated portraits without requiring design of characters or additional software.
01 introduction image processing analysisRumah Belajar
This document provides an introduction to image processing and analysis. It discusses image acquisition, pre-processing techniques like image transforms and enhancement, and applications of image processing. Image transforms like the discrete Fourier transform and discrete cosine transform are used to represent images in different domains. Image enhancement techniques accentuate features to make images more useful for display and analysis. Common techniques include adjusting histograms, using median filters, and performing operations in transform domains.
This document summarizes key concepts about digital image fundamentals. It discusses how images are formed in the eye and sensed by imaging devices. Images are discretized through sampling and quantization to create a digital image represented by a matrix of pixels with discrete intensity values. The document covers characteristics of the human visual system, image resolution, interpolation techniques, arithmetic operations on images like averaging, subtraction and multiplication, and how digital images are represented and stored in memory.
The document provides an overview of digital image processing. It discusses why DIP is needed, defines what a digital image is, and outlines the basic steps of digitizing an image through sampling and quantization. It also describes several applications of DIP in industries like traffic control and management, entertainment, and medicine. The document aims to introduce readers to the fundamental concepts and objectives of the field of digital image processing.
Spandana image processing and compression techniques (7840228)indianspandana
This document discusses image processing and compression techniques. It begins by stating the objectives of image processing as sharpening images, minimizing degradation, and reducing the amount of memory needed to store images through compression. It then provides introductions and definitions related to digital image processing. The key stages of digital image processing are described as image acquisition, enhancement, restoration, morphological processing, segmentation, object recognition, representation and description, color image processing, and compression. Image compression aims to reduce the amount of data required to represent a digital image by removing redundant data. The goals and flow of image compression are explained. Finally, different compression techniques such as lossless compression using run-length encoding and lossy compression are outlined.
The document describes the Colour Imaging Lab at the University of Granada in Spain. The lab conducts research in areas related to color vision, color images, color constancy, and using RGB cameras to recover spectral information. It has permanent staff and PhD students. It has published papers in international journals and conferences and worked on projects funded by the Spanish and Andalusian governments and private companies. The lab has various instruments including tunable liquid crystal filters, cameras, spectroradiometers, and a 3D scanner. It also teaches courses and hosts international students and thesis students.
Digital image processing focuses on improving images for human interpretation and machine perception. It involves key stages like acquisition, enhancement, restoration, morphological processing, segmentation, and representation. Applications include medical imaging, industrial inspection, law enforcement, and human-computer interfaces. While digital images allow for faster and more efficient processing than analog images, limitations include reduced quality if enlarged beyond a certain file size.
This document provides an overview of visual object recognition. It begins with an introduction explaining why object recognition is a challenging problem and discusses the importance of recognizing objects from different viewpoints, scales, textures, etc. It then describes how recognition can be achieved using local image features rather than analyzing the whole object. The document focuses on the Scale Invariant Feature Transform (SIFT) approach, outlining the key stages of detecting local features, generating invariant representations of those features, and verifying matches between images based on geometric configuration. Overall, the summary provides a high-level view of object recognition techniques with a focus on the seminal SIFT method.
This document summarizes a research paper that proposes a method for converting images and video into portraits and animations using RGB color segmentation. The method involves several steps: edge detection using Sobel operator, blurring the image with Gaussian blur to reduce noise, color segmentation by comparing RGB pixel values to a threshold, and region filling to convert the image into a portrait. The overall goal is to automatically convert still images and video into animated portraits without requiring design of characters or additional software.
01 introduction image processing analysisRumah Belajar
This document provides an introduction to image processing and analysis. It discusses image acquisition, pre-processing techniques like image transforms and enhancement, and applications of image processing. Image transforms like the discrete Fourier transform and discrete cosine transform are used to represent images in different domains. Image enhancement techniques accentuate features to make images more useful for display and analysis. Common techniques include adjusting histograms, using median filters, and performing operations in transform domains.
This document summarizes key concepts about digital image fundamentals. It discusses how images are formed in the eye and sensed by imaging devices. Images are discretized through sampling and quantization to create a digital image represented by a matrix of pixels with discrete intensity values. The document covers characteristics of the human visual system, image resolution, interpolation techniques, arithmetic operations on images like averaging, subtraction and multiplication, and how digital images are represented and stored in memory.
The document provides an overview of digital image processing. It discusses why DIP is needed, defines what a digital image is, and outlines the basic steps of digitizing an image through sampling and quantization. It also describes several applications of DIP in industries like traffic control and management, entertainment, and medicine. The document aims to introduce readers to the fundamental concepts and objectives of the field of digital image processing.
This document discusses image restoration using Kriging interpolation technique. It begins with an abstract that introduces Kriging interpolation as a novel statistical image restoration algorithm. The introduction provides background on image restoration and discusses traditional diffusion-based techniques. The proposed methodology section outlines the steps of the technique, which includes preprocessing to remove noise, then using either median diffusion or Kriging interpolation for image interpolation. A comparative analysis is conducted using PSNR, SSIM, and RMSE to evaluate which method performs better. The preprocessing section defines different types of noise that can affect images and noise removal methods.
Digital images can be represented as a two-dimensional matrix of pixels, where each pixel has a discrete location and value. There are three fundamental steps in digital image processing: 1) image acquisition, 2) image enhancement to improve image quality, and 3) image restoration to repair degraded images based on models of image degradation. Additional steps include color image processing, compression, morphological processing, segmentation to separate images into objects, and representation/description to convert raw pixel data into a computer-processable form.
This document provides an overview of digital image processing. It discusses key concepts like image types (intensity, binary, indexed, RGB), image file formats (TIFF, JPEG), image resolutions, and the steps involved in digital image processing. The MATLAB Image Processing Toolbox is also mentioned as a tool for performing operations on images like visualization, analysis, and processing. Edge detection is highlighted as an important but difficult task in digital image processing.
1) The document describes the design of a visual object detection framework capable of rapidly processing images while achieving high detection rates. It begins with a 2D face detection system and extends it to handle colored, multi-pose and 3D images.
2) Key aspects of the system include using Viola-Jones for initial 2D frontal face detection, extracting 3D models from video using structure from motion, and generating frontal views to recognize faces.
3) Experimental results show about a 40% improvement in matching performance by using the 3D models compared to non-frontal 2D frames. The system achieved accuracy comparable to other leading systems and has applications in medical imaging, surveillance, and license plate recognition.
This document describes an efficient approach to identifying design patterns in source code using bit-vector algorithms. It first transforms code and patterns into string representations. It then uses an iterative bit-vector algorithm to match code strings to pattern strings and identify occurrences. The approach was tested on three programs and found to identify patterns much faster than existing constraint-based techniques, especially when incorporating approximations. Future work aims to improve precision by combining with metrics and adding more relationship and dynamic information.
This document summarizes a new approach for optimizing invisible image watermarking using symmetric key algorithms. The approach hides information by dividing a message evenly between two images and manipulating the least significant bit of pixels. It also encrypts the image addresses as a key using DES or AES algorithms. The method embeds data in the spatial domain by changing pixel values. This provides improved security compared to single image watermarking by maximizing the number of images used to hide data. Experimental results show encrypted images cannot be viewed without decryption using the user key, and secret messages can be extracted from watermarked images.
This document presents a method for identity recognition using edge suppression. It aims to recognize identity even under severe shadows. The method uses edge suppression through affine transformation and gradient field calculation to determine light source positions. K-nearest neighbor classification is used for matching identities in databases, along with principal component analysis for feature extraction. Diagonally projecting tensors are applied to suppress edges and remove shadows from images. The method is evaluated on standard databases and is proposed to work for real-time identity recognition applications.
This document summarizes an image watermarking algorithm in the discrete wavelet transform (DWT) domain for image authentication. The algorithm first converts the input image to grayscale and divides the Y component into blocks. It then applies a 2-level DWT and uses a Canny edge detector to generate a watermark from the image contours. The watermark is embedded in the DWT coefficients after applying an Arnold transform for security. In extraction, the watermark is recovered from the DWT coefficients and compared to the original to authenticate the image. Experiments show the algorithm is effective against attacks like image pasting while maintaining high PSNR for perceptual invisibility of the watermark.
Computer graphics deals with generating, manipulating, and displaying images using computers. It has revolutionized graphic design by moving the industry from physical tools like pasteboards to digital tools using computers and software. Now designers use computers and graphics software to do everything from page layouts to preparing documents for printing. Some key features of computer graphics include vector graphics which use lines and shapes, raster graphics which use pixels, and transformations which allow simulated spatial manipulation of objects.
The document discusses the fundamental steps in digital image processing. It describes 7 key steps: (1) image acquisition, (2) image enhancement, (3) image restoration, (4) color image processing, (5) wavelets and multiresolution processing, (6) image compression, and (7) morphological processing. For each step, it provides brief explanations of the techniques and purposes involved in digital image processing.
Hi-Tech provides building energy modeling and analysis services. Check the key points of our services below.
1) To qualify the building for EPACT Certification using eQuest.
2) Interior, Exterior & Day Lighting reports for existing & proposed design.
3) Review of existing buildings, HVAC systems, lighting etc. & possibly save up to 60% in the proposed design, better than the Code.
4) Comparison of existing & proposed systems with respect to the Baseline Appendix-G ASHRAE 90.1.
5) Technical assistance to reduce energy consumption as per international standards (i.e. ASHRAE 90.1), local authority regulation & as per client’s requirements.
6) Software Used for Energy Modeling : eQuest 3.64, DiaLux, COMcheck & AutoCAD.
For any queries please email us at info@hitechcaddservices.com
This document provides an overview of a digital image processing lecture given by Dr. Moe Moe Myint at Technological University in Kyaukse, Myanmar. It includes information about the instructor's contact information and office hours. The document then summarizes the contents of Chapter 2, which covers topics like visual perception, light and the electromagnetic spectrum, image sensing and acquisition, and basic relationships between pixels. Examples and diagrams are provided to illustrate concepts like the structure of the human eye, image formation, brightness adaptation, and the electromagnetic spectrum. Optical illusions are also discussed as examples of how visual perception does not always match physical stimuli.
SIGGRAPH ASIA 2012 Stereoscopic Cloning Presentation SlideI-Chao Shen
This is the presentation slide of paper : Perspective-Aware Warping for Seamless Stereoscopic Image Cloning.
It is made by Sheng-Jie Luo, National Taiwan University.
Please refer to http://www.cmlab.csie.ntu.edu.tw/~forestking/research/SIGA12-StereoCloning/ for more detail.
IRJET- Design and Implementation of ATM Security System using Vibration Senso...IRJET Journal
This document discusses implementing bi-histogram equalization for contrast enhancement on the Android platform. It begins with an introduction to histogram equalization and its drawback of changing image brightness. It then presents bi-histogram equalization as an approach to overcome this by decomposing the image into two sub-images based on the mean and equalizing them independently to preserve the mean brightness. The paper outlines implementing various steps like image acquisition, preprocessing, and bi-histogram equalization on Android. It shows output images with enhanced visibility compared to the originals, avoiding the flattening property of standard histogram equalization.
This document discusses how a brain-computer interface (BCI) works. It explains that a BCI detects sensorimotor rhythms in the mu and beta frequency bands in the sensorimotor cortex using EEG or ECoG. It describes how motor imagery causes event-related desynchronization and synchronization of these rhythms. A BCI also requires training users to generate distinguishable brain patterns through motor imagery without external stimuli. Signal processing techniques are used to extract relevant features and classify patterns for device control.
This document summarizes a research paper that proposes a new digital image watermarking technique using discrete wavelet transform and singular value decomposition (DWT-SVD). The technique embeds a watermark in the high frequency subbands of an image after applying DWT and SVD. Experimental results show the watermarked images have high quality as measured by PSNR. The extracted watermarks are robust to common image distortions like noise, filtering, and cropping as measured by normalized cross correlation. A comparison shows the proposed technique provides better image quality and watermark extraction than a previous DWT-based method. The technique could provide copyright protection for digital images.
Novel DCT based watermarking scheme for digital imagesIDES Editor
There is an ever growing interest in copyright
protection of multimedia content, thus digital
watermarking techniques are widely practiced. Due to
the internet connectivity and digital libraries the
research interest of protecting digital content
watermarking is extensively researched. In this paper
we present a novel watermark generation scheme
based on the histogram of the image and apply it to the
original image in the transform(DCT) domain. Further
we study the performance of the watermark against
some common attacks that can take place with images.
Experimental results show that the embedded
watermark is imperceptible and image quality is not
degraded.
This document is a lecture on advanced computer graphics prepared by Meera N. Hapaliya of V.V.P. Engineering College. It covers topics such as achromatic and chromatic light, the electromagnetic spectrum, color models for raster graphics including RGB, CMY, YIQ, HLS, and HSV, gamma correction, image quantization and halftoning techniques like dithering and ordered dither. The document provides definitions and examples to explain key concepts in representing and processing digital color images.
IRJET- Proposed Approach for Layout & Handwritten Character Recognization in OCRIRJET Journal
This document proposes an approach for layout analysis and handwritten character recognition in optical character recognition systems. It discusses challenges in recognizing text in documents containing both printed and handwritten text, as well as non-text elements like images. The proposed approach uses document segmentation techniques like connected component analysis and block segmentation to separate text and non-text regions, and further separates printed and handwritten text regions. It aims to apply these techniques to handwritten bills to allow segmentation and analysis of the bills in a user-friendly way for small business owners. The key steps involve preprocessing, text/non-text segmentation, layer separation for printed/handwritten text, and block segmentation using a run-length smearing algorithm and white space detection.
The document discusses quality management and improving customer satisfaction. It defines key quality elements for products and services, including performance, features, reliability, conformance, durability, serviceability, and aesthetics. It also outlines the quality cycle of planning, inspection, and improvement. Quality elements are analyzed using a technique called 5 Whys to identify root causes of issues. The document provides an overview of strategies for defining customer needs, inspecting quality parameters, and maintaining quality elements.
The document discusses image processing and its importance. Image processing learns from the human mechanism of seeing by employing algorithms to gain skills similar to human vision. This allows machines to do tasks like counting stars with a simple camera, estimating distances and temperatures, measuring object speeds, facial authentication, face description, motion detection, and object recognition by attributes like shape, size, and area.
This document outlines the key characteristics of a professional learning community (PLC). It discusses how a PLC focuses on student learning through collaborative teams who work interdependently and are mutually accountable. It also emphasizes that a PLC takes an action-oriented approach through continuous cycles of gathering evidence, developing and implementing strategies, analyzing their impact, and applying lessons learned to further improve student outcomes. Finally, it notes that organizations should begin the work of a PLC by taking action, rather than solely preparing through reading or training, in order to more effectively help all students learn at high levels.
This document discusses image restoration using Kriging interpolation technique. It begins with an abstract that introduces Kriging interpolation as a novel statistical image restoration algorithm. The introduction provides background on image restoration and discusses traditional diffusion-based techniques. The proposed methodology section outlines the steps of the technique, which includes preprocessing to remove noise, then using either median diffusion or Kriging interpolation for image interpolation. A comparative analysis is conducted using PSNR, SSIM, and RMSE to evaluate which method performs better. The preprocessing section defines different types of noise that can affect images and noise removal methods.
Digital images can be represented as a two-dimensional matrix of pixels, where each pixel has a discrete location and value. There are three fundamental steps in digital image processing: 1) image acquisition, 2) image enhancement to improve image quality, and 3) image restoration to repair degraded images based on models of image degradation. Additional steps include color image processing, compression, morphological processing, segmentation to separate images into objects, and representation/description to convert raw pixel data into a computer-processable form.
This document provides an overview of digital image processing. It discusses key concepts like image types (intensity, binary, indexed, RGB), image file formats (TIFF, JPEG), image resolutions, and the steps involved in digital image processing. The MATLAB Image Processing Toolbox is also mentioned as a tool for performing operations on images like visualization, analysis, and processing. Edge detection is highlighted as an important but difficult task in digital image processing.
1) The document describes the design of a visual object detection framework capable of rapidly processing images while achieving high detection rates. It begins with a 2D face detection system and extends it to handle colored, multi-pose and 3D images.
2) Key aspects of the system include using Viola-Jones for initial 2D frontal face detection, extracting 3D models from video using structure from motion, and generating frontal views to recognize faces.
3) Experimental results show about a 40% improvement in matching performance by using the 3D models compared to non-frontal 2D frames. The system achieved accuracy comparable to other leading systems and has applications in medical imaging, surveillance, and license plate recognition.
This document describes an efficient approach to identifying design patterns in source code using bit-vector algorithms. It first transforms code and patterns into string representations. It then uses an iterative bit-vector algorithm to match code strings to pattern strings and identify occurrences. The approach was tested on three programs and found to identify patterns much faster than existing constraint-based techniques, especially when incorporating approximations. Future work aims to improve precision by combining with metrics and adding more relationship and dynamic information.
This document summarizes a new approach for optimizing invisible image watermarking using symmetric key algorithms. The approach hides information by dividing a message evenly between two images and manipulating the least significant bit of pixels. It also encrypts the image addresses as a key using DES or AES algorithms. The method embeds data in the spatial domain by changing pixel values. This provides improved security compared to single image watermarking by maximizing the number of images used to hide data. Experimental results show encrypted images cannot be viewed without decryption using the user key, and secret messages can be extracted from watermarked images.
This document presents a method for identity recognition using edge suppression. It aims to recognize identity even under severe shadows. The method uses edge suppression through affine transformation and gradient field calculation to determine light source positions. K-nearest neighbor classification is used for matching identities in databases, along with principal component analysis for feature extraction. Diagonally projecting tensors are applied to suppress edges and remove shadows from images. The method is evaluated on standard databases and is proposed to work for real-time identity recognition applications.
This document summarizes an image watermarking algorithm in the discrete wavelet transform (DWT) domain for image authentication. The algorithm first converts the input image to grayscale and divides the Y component into blocks. It then applies a 2-level DWT and uses a Canny edge detector to generate a watermark from the image contours. The watermark is embedded in the DWT coefficients after applying an Arnold transform for security. In extraction, the watermark is recovered from the DWT coefficients and compared to the original to authenticate the image. Experiments show the algorithm is effective against attacks like image pasting while maintaining high PSNR for perceptual invisibility of the watermark.
Computer graphics deals with generating, manipulating, and displaying images using computers. It has revolutionized graphic design by moving the industry from physical tools like pasteboards to digital tools using computers and software. Now designers use computers and graphics software to do everything from page layouts to preparing documents for printing. Some key features of computer graphics include vector graphics which use lines and shapes, raster graphics which use pixels, and transformations which allow simulated spatial manipulation of objects.
The document discusses the fundamental steps in digital image processing. It describes 7 key steps: (1) image acquisition, (2) image enhancement, (3) image restoration, (4) color image processing, (5) wavelets and multiresolution processing, (6) image compression, and (7) morphological processing. For each step, it provides brief explanations of the techniques and purposes involved in digital image processing.
Hi-Tech provides building energy modeling and analysis services. Check the key points of our services below.
1) To qualify the building for EPACT Certification using eQuest.
2) Interior, Exterior & Day Lighting reports for existing & proposed design.
3) Review of existing buildings, HVAC systems, lighting etc. & possibly save up to 60% in the proposed design, better than the Code.
4) Comparison of existing & proposed systems with respect to the Baseline Appendix-G ASHRAE 90.1.
5) Technical assistance to reduce energy consumption as per international standards (i.e. ASHRAE 90.1), local authority regulation & as per client’s requirements.
6) Software Used for Energy Modeling : eQuest 3.64, DiaLux, COMcheck & AutoCAD.
For any queries please email us at info@hitechcaddservices.com
This document provides an overview of a digital image processing lecture given by Dr. Moe Moe Myint at Technological University in Kyaukse, Myanmar. It includes information about the instructor's contact information and office hours. The document then summarizes the contents of Chapter 2, which covers topics like visual perception, light and the electromagnetic spectrum, image sensing and acquisition, and basic relationships between pixels. Examples and diagrams are provided to illustrate concepts like the structure of the human eye, image formation, brightness adaptation, and the electromagnetic spectrum. Optical illusions are also discussed as examples of how visual perception does not always match physical stimuli.
SIGGRAPH ASIA 2012 Stereoscopic Cloning Presentation SlideI-Chao Shen
This is the presentation slide of paper : Perspective-Aware Warping for Seamless Stereoscopic Image Cloning.
It is made by Sheng-Jie Luo, National Taiwan University.
Please refer to http://www.cmlab.csie.ntu.edu.tw/~forestking/research/SIGA12-StereoCloning/ for more detail.
IRJET- Design and Implementation of ATM Security System using Vibration Senso...IRJET Journal
This document discusses implementing bi-histogram equalization for contrast enhancement on the Android platform. It begins with an introduction to histogram equalization and its drawback of changing image brightness. It then presents bi-histogram equalization as an approach to overcome this by decomposing the image into two sub-images based on the mean and equalizing them independently to preserve the mean brightness. The paper outlines implementing various steps like image acquisition, preprocessing, and bi-histogram equalization on Android. It shows output images with enhanced visibility compared to the originals, avoiding the flattening property of standard histogram equalization.
This document discusses how a brain-computer interface (BCI) works. It explains that a BCI detects sensorimotor rhythms in the mu and beta frequency bands in the sensorimotor cortex using EEG or ECoG. It describes how motor imagery causes event-related desynchronization and synchronization of these rhythms. A BCI also requires training users to generate distinguishable brain patterns through motor imagery without external stimuli. Signal processing techniques are used to extract relevant features and classify patterns for device control.
This document summarizes a research paper that proposes a new digital image watermarking technique using discrete wavelet transform and singular value decomposition (DWT-SVD). The technique embeds a watermark in the high frequency subbands of an image after applying DWT and SVD. Experimental results show the watermarked images have high quality as measured by PSNR. The extracted watermarks are robust to common image distortions like noise, filtering, and cropping as measured by normalized cross correlation. A comparison shows the proposed technique provides better image quality and watermark extraction than a previous DWT-based method. The technique could provide copyright protection for digital images.
Novel DCT based watermarking scheme for digital imagesIDES Editor
There is an ever growing interest in copyright
protection of multimedia content, thus digital
watermarking techniques are widely practiced. Due to
the internet connectivity and digital libraries the
research interest of protecting digital content
watermarking is extensively researched. In this paper
we present a novel watermark generation scheme
based on the histogram of the image and apply it to the
original image in the transform(DCT) domain. Further
we study the performance of the watermark against
some common attacks that can take place with images.
Experimental results show that the embedded
watermark is imperceptible and image quality is not
degraded.
This document is a lecture on advanced computer graphics prepared by Meera N. Hapaliya of V.V.P. Engineering College. It covers topics such as achromatic and chromatic light, the electromagnetic spectrum, color models for raster graphics including RGB, CMY, YIQ, HLS, and HSV, gamma correction, image quantization and halftoning techniques like dithering and ordered dither. The document provides definitions and examples to explain key concepts in representing and processing digital color images.
IRJET- Proposed Approach for Layout & Handwritten Character Recognization in OCRIRJET Journal
This document proposes an approach for layout analysis and handwritten character recognition in optical character recognition systems. It discusses challenges in recognizing text in documents containing both printed and handwritten text, as well as non-text elements like images. The proposed approach uses document segmentation techniques like connected component analysis and block segmentation to separate text and non-text regions, and further separates printed and handwritten text regions. It aims to apply these techniques to handwritten bills to allow segmentation and analysis of the bills in a user-friendly way for small business owners. The key steps involve preprocessing, text/non-text segmentation, layer separation for printed/handwritten text, and block segmentation using a run-length smearing algorithm and white space detection.
The document discusses quality management and improving customer satisfaction. It defines key quality elements for products and services, including performance, features, reliability, conformance, durability, serviceability, and aesthetics. It also outlines the quality cycle of planning, inspection, and improvement. Quality elements are analyzed using a technique called 5 Whys to identify root causes of issues. The document provides an overview of strategies for defining customer needs, inspecting quality parameters, and maintaining quality elements.
The document discusses image processing and its importance. Image processing learns from the human mechanism of seeing by employing algorithms to gain skills similar to human vision. This allows machines to do tasks like counting stars with a simple camera, estimating distances and temperatures, measuring object speeds, facial authentication, face description, motion detection, and object recognition by attributes like shape, size, and area.
This document outlines the key characteristics of a professional learning community (PLC). It discusses how a PLC focuses on student learning through collaborative teams who work interdependently and are mutually accountable. It also emphasizes that a PLC takes an action-oriented approach through continuous cycles of gathering evidence, developing and implementing strategies, analyzing their impact, and applying lessons learned to further improve student outcomes. Finally, it notes that organizations should begin the work of a PLC by taking action, rather than solely preparing through reading or training, in order to more effectively help all students learn at high levels.
This document contains a presentation by Aditya Kurniawan about PLC technologies. It includes Aditya's curriculum vitae, which notes his experience as a PLC programmer and quality assurance engineer. The presentation covers fundamentals of PLC technologies, including introductions to PLC systems, programming languages, input and output modules, and the CPU unit. It also explains discrete control automation and basic logic functions like AND, OR, NOT, NAND, XOR, and XNOR gates.
1. The document discusses the use of ultrasonic rangefinders for mobile robot sensing and collision avoidance.
2. It explains how the radiation cone of the ultrasonic sensor and the measured distance relates to the actual clearance around the robot given its diameter.
3. An example is provided of calculating the actual radiation distance of 0.24 meters given a measured distance of 1 meter from an ultrasonic sensor with a 45 degree radiation cone mounted on a robot with a 0.2 meter diameter.
The document provides an overview of the key features and functionality of the Edmodo social learning platform, including how to:
1) Set up an account as a teacher and create classes/groups for students.
2) Manage student and parent accounts, including distributing unique parent codes to allow parents to view their child's activity.
3) Post various content like notes, assignments, quizzes and polls, and organize content in a library with folders.
4) Customize group settings and control features like moderating posts and default access levels for members.
This document outlines an Animoto project that defines Animoto, who can use it, how it works, installation, examples, features, advantages, disadvantages, problems, and additional resources. Animoto allows users to create professional-looking videos from photos and includes editing tools and music libraries. It can be used by individuals and businesses and shared on social media. While free for basic use, extended videos require a paid plan.
Demand for rubber gloves is still growing strongly at an annual rate of 8-10% despite currently high glove prices. Global demand is expected to reach 155 billion pieces by 2011, driven by increased healthcare awareness and reforms. Malaysia supplies 63% of global demand and the top 6 Malaysian glove companies have 54% of the global market share. Developed countries prefer powder-free natural rubber gloves which make up 74% of exports, while developing markets like China and India offer future growth potential. The rubber glove industry faces high barriers to entry and continues improving production technologies, while latex prices may gradually stabilize after peaking recently.
The document introduces mobile robot locomotion. It defines a robot as an electromechanical system that can sense its surroundings, perform tasks through locomotion or manipulation, be reprogrammed, and interact with humans autonomously. Mobile robots include wheeled, legged, aerial, underwater, and humanoid robots. The position, orientation, and posture of mobile robots are described in relation to Cartesian coordinates. Motion parameters like wheel distance, diameter, and rotational speed are discussed. Different types of wheeled mobile robots and their motion principles are outlined.
The document provides instructions for creating assessments using Google Forms. It outlines how to create and name a form, add different types of questions, include identifying information as the first questions, change the theme, preview the form, administer the test by sending the link via email or posting to a class site, and view the response data in a spreadsheet. The instructions are meant to guide teachers through setting up, distributing, and reviewing results of classroom assessments created in Google Forms.
Programmable logic controllers (PLCs) are solid-state industrial computer control systems that can store instructions to control machines and processes. PLCs are capable of controlling binary inputs and outputs, performing arithmetic and data manipulation, sequencing, timing, counting, and communication. Modern PLCs are modular, scalable, and programmable via simple programming methods to control industrial automation applications. PLCs use logic gates and binary concepts to read inputs, execute program instructions, and control outputs.
SXSW 2016 Music Conference: Creating Custom Songs for Film, TV, Trailers & AdsAmanda Krieg
The document discusses creating original songs for use in film, TV, advertisements and trailers. It provides tips for what makes a song suitable for these mediums, such as having a clear hook and helping to tell the story without being distracting. The process for creating such a song involves researching the project, writing the song, recording it, and submitting it for revisions. Common pitfalls include being too direct or telling someone else's story rather than enhancing the visuals. Advice includes doing research, understanding the client's vision, and being flexible.
Dokumen tersebut merangkum proses pengajuan dan pengelolaan bantuan mahasiswa berupa Bantuan Modal Tidak Mundur (BMTM) melalui 3 instansi yaitu Direktorat Kemahasiswaan, Direktorat Akademik, dan DKM Alfurqon. Prosesnya dimulai dari mahasiswa mengajukan permohonan, dilakukan verifikasi dokumen, dilanjutkan visitasi, penetapan penerima, penandatanganan perjanjian, pemberian dana
SXSW 2016 Film Conference: Making (and Making the Most of) Your Music BudgetAmanda Krieg
The document provides advice from music industry professionals on budgeting for and obtaining music for films. It recommends budgeting 2-5% of the total film budget for music. Hiring a composer or using a music library can provide customized music within a budget. A music supervisor can help navigate the clearance process and leverage industry connections to access affordable music sources. Planning, knowing what music is needed, and having paperwork in order are also advised.
The document discusses estimated market sizes in the hundreds of millions to billions and recommends dividing estimates by 1,000 to calculate a 0.1% target market share. It also notes that a major pilot test was conducted in Porto, Portugal involving 200 locations and enrolling 1,300 people.
This document introduces a solution called QGS that links nail salons with customers. QGS allows customers to book appointments online or receive reminders, and gives salons tools to manage appointments, promotions and customer databases. It aims to provide salons with more customers and better management of resources. QGS plans to expand to other beauty services like hair and spas. The business model involves monthly merchant fees, revenue from deals and promotions, data sharing between merchants and vendors, recruitment, advertisements and data mining.
The document discusses seven basic quality tools: check sheets, stratification, histograms, Pareto charts, Ishikawa diagrams, scatter diagrams, and control charts. It provides examples and explanations of how to implement each tool, including how to classify data, indicate locations and frequencies, and analyze relationships between variables. Check sheets involve tallying traits, stratification organizes data into classifications, histograms and Pareto charts display distributions graphically, and scatter diagrams and control charts assess correlations. Ishikawa diagrams map potential causes for effects through a cause-and-effect tree structure.
Pneumatic systems use air pressure and flow to generate force and movement. They are powered by compressed air and include components like cylinders, valves, and actuators to control airflow and movement. Common pneumatic components include single-acting and double-acting cylinders to produce linear motion, and directional valves and logic valves to control airflow. Pneumatic systems tend to be slower but stronger than electric systems but can handle heavy loads and harsh environments.
The document discusses several case studies of applying machine learning to different problems:
1) Classifying images as day or night using a convolutional neural network.
2) Face verification using deep neural networks to encode faces and compare encodings.
3) Neural style transfer to generate artistic images by combining the content of one image and the style of another, using neural network features and gram matrices.
4) Various techniques are discussed for problems like face identification, clustering, and trigger word detection from audio. The case studies illustrate different modeling decisions needed for machine learning projects.
The document discusses the fundamentals of digital image processing. It defines a digital image as a 2D function where amplitude at each point represents intensity or gray level. A digital image is composed of pixels which are discrete image elements. Image processing includes low-level tasks like noise reduction, mid-level tasks like segmentation, and high-level tasks like object recognition. Mathematical representation of a digital image involves illumination and reflectance components. Intensity at each point in a monochrome image represents its gray level value within the gray scale range from minimum to maximum.
This document provides an overview of digital image processing. It defines what an image is, noting that an image is a spatial representation of a scene represented as an array of pixels. Digital image processing refers to processing digital images on a computer. The key steps in digital image processing are image acquisition, enhancement, restoration, compression, morphological processing, segmentation, representation, and recognition. Digital image processing has many applications including medical imaging, traffic monitoring, biometrics, and computer vision.
This document provides lecture notes on digital image processing. It discusses key topics such as the definition of digital images and how they are represented, the fundamental steps in digital image processing including image acquisition, enhancement, restoration, and compression, the components of an image processing system including sensors, hardware, software, storage and display, and elements of visual perception including the structure of the human eye and how light is sensed by the retina.
Vector images are formed by independent geometric objects like lines and curves defined by mathematical values, whereas bitmap images are formed by pixels. Vector images generally require less memory than bitmaps and can be enlarged without losing precision. When displayed on a screen, the computer must convert the vector image to a bitmap. Common software for working with vector images includes Inkscape, Adobe Illustrator, CorelDRAW, and AutoCAD.
The document discusses three major computer vision tasks solved using deep learning: image classification, object detection, and embeddings. Image classification involves categorizing whole images into classes. Object detection combines classification and localization to identify multiple objects within an image. Embeddings represent inputs as vectors to capture semantics and preserve similarity. Pre-trained models and large datasets are used to train systems that can then be applied to problems like medical diagnosis, quality control, and autonomous vehicles.
Digital images are represented as a finite set of digital values called pixels arranged in a grid. There are several types of digital images including grayscale, RGB color, and binary. Digital image processing involves tasks like image enhancement, restoration, compression, and analysis. The key steps in digital image processing are image acquisition, representation and description, segmentation, recognition and display. The human visual system perceives brightness in a logarithmic fashion and can adapt to a wide range of light intensities. Proper sampling and quantization are required to convert a natural image into a digital image without loss of information.
P04 restricted boltzmann machines cvpr2012 deep learning methods for visionzukun
The document summarizes deep learning methods for computer vision, specifically discussing restricted Boltzmann machines (RBMs), deep belief networks (DBNs), and their training algorithms. RBMs and DBNs are unsupervised learning models that can learn feature representations from unlabeled data. DBNs are deep neural networks composed of multiple RBMs trained in a greedy layer-wise fashion. The training algorithms, like contrastive divergence, maximize the likelihood of the data to learn the model parameters.
This document discusses single object tracking and velocity determination. It begins with an introduction and objectives of the project which is to develop an algorithm for tracking a single object and determining its velocity in a sequence of video frames. It then provides details on preprocessing techniques like mean filtering, Gaussian smoothing and median filtering to reduce noise. It describes segmentation methods including histogram-based, single Gaussian background and frame difference approaches. Feature extraction methods like edges, bounding boxes and color are explained. Object detection using optical flow and block matching is covered. Finally, it discusses tracking and calculating velocity of the moving object. MATLAB is introduced as a technical computing language for solving these types of problems.
A Gesture Based Digital Art with Colour Coherence Vector AlgorithmIRJET Journal
This document describes a gesture-based digital art system using a color coherence vector algorithm. The system uses gesture recognition to track colored markers on a user's fingers to allow drawing in the air. A Raspberry Pi processes images from a webcam to recognize gestures and display corresponding drawings on an LCD screen in real-time. The system is intended to provide a convenient way to create digital art wirelessly using natural hand gestures.
General Review Of Algorithms Presented For Image SegmentationMelissa Moore
This paper proposes a system for recognizing human facial actions from images using image processing and machine learning techniques. The system first detects faces in images using a pretrained detector. Facial landmarks are then extracted to locate features like eyes, nose, mouth etc. Features extracted from the landmarks are used to recognize six basic facial expressions (happy, sad, angry, surprised, disgusted and neutral). The system is trained on a facial expression dataset to learn the patterns associated with each expression. The trained model can then be used to automatically recognize the expression in new input images. The proposed system has applications in areas like human-computer interaction, lie detection, sentiment analysis etc.
Labcamp - working with image processingRenato Souza
This document discusses working with image processing. It begins with an introduction to digital images and how they are formed. It then covers the different levels of image processing - low-level (restoration, enhancement), mid-level (segmentation, classification) and high-level (making sense of recognized objects). OpenCV, an open source library for computer vision and machine learning, is also introduced. The document concludes with resources for OpenCV and an overview of tutorials for setting up OpenCV on Eclipse and examples exercises for webcam applications with and without face detection.
This document provides an overview of digital image processing and image compression techniques. It defines what a digital image is, discusses the advantages and disadvantages of digital images over analog images. It describes the fundamental steps in digital image processing as well as types of data redundancy that can be exploited for image compression, including coding, interpixel, and psychovisual redundancy. Common image compression models and lossless compression techniques like Lempel-Ziv-Welch coding are also summarized.
This document provides an introduction to fundamentals of image processing. It defines key concepts such as digital images, image sampling, and common image processing tools. Digital images are represented as arrays of pixels with integer brightness values. Common image processing tools introduced include convolution, Fourier transforms, and different types of image operations and neighborhoods that can be used. The document also discusses video standards and parameters for digitized video images.
The document discusses digital image processing and provides an overview of key concepts. It defines digital and analog images and explains how digital images are represented by pixels. It outlines fundamental steps in digital image processing like image acquisition, enhancement, restoration, morphological processing, segmentation, representation, compression and object recognition. It also discusses applications in areas like remote sensing, medical imaging, film and video effects.
This document provides an overview of the topics that will be covered in lectures 1-3 of the course MATHEMATICAL IMAGING TECHNIQUES. The lectures will cover fundamentals of image formation, sampling and quantization, spatial domain filtering techniques including intensity transformations, histogram equalization, and smoothing/sharpening filters. Frequency domain filtering including the Fourier transform and filters such as lowpass, highpass, and bandpass will also be discussed. Recommended textbooks and reference materials are provided.
IRJET - Computer-Assisted ALL, AML, CLL, CML Detection and Counting for D...IRJET Journal
This document describes a computer-assisted method for detecting and counting four types of blood cancer (ALL, AML, CLL, CML) from microscopic blood images. The method first segments the image to identify white blood cells, then extracts lymphocytes. Shape and color features of the lymphocytes are used to classify them as normal or blast cells using SVM. The system was found to be more accurate and fast compared to manual identification methods. It aims to automatically diagnose blood cancers from images in a time-efficient and accurate manner.
This document provides information about digital image processing. It defines digital image processing as manipulating digital images through a computer, which is a subfield of signals and systems that focuses on images. The document lists some basic knowledge required for digital image processing, including signals and systems, calculus, probability, and basic programming skills. It also outlines several applications of digital image processing such as medical imaging, remote sensing, and pattern recognition. Finally, it provides some examples of companies that employ digital image processing.
Similar to Pertemuan 1. introduction to image processing (20)
The document introduces mobile robot locomotion. It defines a robot as an electromechanical system that can sense its surroundings, carry out tasks through locomotion or manipulation, be reprogrammable, and interact with humans autonomously. Mobile robots are categorized as wheeled, legged, aerial, underwater, or humanoid. Their position is defined by coordinates (X,Y) on a plane, and orientation by degrees from 0-360. A robot's posture combines its position and orientation as (X,Y,Φ). Motion parameters include wheel distance, diameter, and rotational speed. Wheeled robots can move linearly, in circles, or change center point, and are classified by wheel configuration.
The document outlines a class flow scenario for an English program that teaches simple past and present tenses. For simple past tense, the class includes introductory sessions, uploading syllabus and guidelines, embedding presentations and videos on the topic, interactive class sessions using Big Blue Button, assignments, exams, and uploading results. A similar process is followed for simple present tense, and certificates are sent after covering both tenses.
The document discusses mechanical joints and their degrees of freedom. It describes two common joints - the prismatic joint and revolute joint. The prismatic joint allows for single-axis sliding motion and is used in devices like cylinders. The revolute joint allows for rotation about a single axis. It also defines total degrees of freedom as the 6 possible motions in 3D space (3 translations and 3 rotations) and controllable degrees of freedom as the subset that can be controlled. An example is given of a non-holonomic robot that has 2 total DOF but can only control 1 DOF through its revolute joint.
Pneumatic systems use air pressure and flow to generate force and movement. They are powered by compressed air and include components like cylinders, valves, and actuators to control airflow and movement. Common pneumatic components include single-acting and double-acting cylinders to convert air pressure into linear motion, as well as directional valves and logic valves to control airflow. Pneumatic systems tend to be slower but stronger than electric systems.
The document outlines a code of conduct for an online class that requires students to use their real photo, discuss only course material in formal language, avoid promoting personal websites or posting photos/videos without permission, and actively attend all classes to complete the course.
The document provides guidelines for students posting and replying to messages in an online class forum. Students should post questions for the whole group about assignments and instructions, and direct personal questions only to teachers. Posts should stay on topic without teasing, bullying, or gossip. When replying, students should not answer if unsure or if someone else has already responded correctly. Any inappropriate content in groups should be reported to teachers. Proper grammar, spelling, and punctuation are expected in posts.
This document provides an introduction to quality tools and strategies, including Six Sigma. It discusses defining critical to quality factors, calculating defects per million opportunities (DPMO), converting DPMO to a Sigma rating, and using the Sigma rating to set defect limits and determine inspection frequency for quality improvement. As an example, it calculates the 2.4 Sigma rating for a company with a DPMO of 161,605 and discusses a plan to upgrade their process to 2.5 Sigma by addressing a gap of 2,950 defects. It also introduces failure modes and effects analysis (FMEA) as a tool for intensive inspection.
The document provides an overview of pneumatic systems, which use compressed air and gas to generate force and movement. It defines pneumatics and compares it to electric systems. It then discusses various pneumatic components like cylinders, valves, actuators and provides diagrams of common components like single-acting cylinders and double-acting cylinders. The document aims to explain the basic understanding and components of pneumatic systems.
1. Dokumen tersebut membahas berbagai teknik dasar pengolahan citra digital seperti kuantisasi, brightness, contrast, inversi, histogram, histogram equalization, filtering, korelasi, dan konvolusi.
The document provides a curriculum vitae for Aditya Kurniawan who works at Politeknik Elektronika - ITS as a lecturer in mechatronics engineering. His areas of specialization include image processing, sensorics, actuation, and quality control. He has work experience in PLC programming, quality assurance engineering, and technical support. He has also participated in several training programs and workshops on topics such as ISO standards, GSM networks, liquid handling, microimaging, and more. The CV concludes with details on course materials for an image processing class covering topics like image formation, enhancement techniques, feature extraction, and assessment methods.
This document contains a presentation by Aditya Kurniawan about hydraulic technologies on heavy equipment. It discusses excavators and shovels as examples, describing their components and movements. It also covers the work envelopes and terrains handled by different heavy equipment. The presentation examines the machines from a mechatronics perspective, analyzing components like booms, buckets, and joints as robotic links and effectors.
This document provides an overview of hydraulics, including comparisons to other systems like pneumatics and electronics, basic hydraulic principles regarding force and pressure, and descriptions of key hydraulic components such as cylinders, valves, pumps, and control systems. It also includes diagrams of common hydraulic symbols.
Electropneumatic systems combine pneumatic actuators and controllers with electric control circuits. Pneumatic actuators include cylinders, motors, and valves, which are powered by compressed air. However, the electric control circuits use electrical components like switches, relays, and programmable logic controllers to control the flow of compressed air and automate pneumatic processes. While pneumatic systems can be complicated to control, electropneumatic systems simplify control with digital electric signals regulating complex pneumatic circuits and multiple actuators.
2. WHAT IS THE DIFFERENCE ?
Image Processing
Computer Vision
Robot Vision
2
Aditya@poltekom.ac.id
3. IMAGE PROCESSING
A process to an image focusing on transforming, encoding and transmitting
the image.
IMAGE IMAGE
3
Aditya@poltekom.ac.id
4. COMPUTER VISION
Computer Vision => media to know the world visually supported by
knowledge strength by computational instrument.
Description /
IMAGE humanized
information
4
Aditya@poltekom.ac.id
5. ROBOT VISION
Robot Vision => a machine with ability to see his environment designed with
workflow algorithm, so it can make a decision and finish the job automatically.
IMAGE Action
5
Aditya@poltekom.ac.id
8. INTRODUCTION
Modern digital technology has made it possible to
manipulate multi-dimensional signals with systems that range
from simple digital circuits to advanced parallel computers.
The goal of this manipulation can be divided into three
categories:
Image Processing
Image in image out
Image Analysis
Image in measurements out
Image Understanding
Image in high-level description out
8
Aditya@poltekom.ac.id
12. INTRODUCTION
We begin with certain basic definitions.
An image defined in the “real world” is
considered to be a function of two real variables, for
example, a(x,y) with a as the amplitude (e.g. brightness)
of the image at the real coordinate position (x,y).
12
Aditya@poltekom.ac.id
13. INTRODUCTION
An image may be considered to contain sub-
images sometimes referred to as regions–of–interest, ROIs,
or simply regions. This concept reflects the fact that
images frequently contain collections of objects each of
which can be the basis for a region.
13
Aditya@poltekom.ac.id
15. INTRODUCTION
Y1 Y2
Regions X1
Of
Interest
X2
15
Aditya@poltekom.ac.id
16. INTRODUCTION
Y1 Y2 Y3 Y4
Regions
Regions Of
Of Interest
Interest X1
X2
16
Aditya@poltekom.ac.id
17. INTRODUCTION
In a sophisticated image processing system it should be possible to
apply specific image processing operations to selected regions. Thus one part
of an image (region) might be processed to suppress motion blur while
another part might be processed to improve color rendition.
17
Aditya@poltekom.ac.id
19. DIGITAL IMAGE DEFINITIONS
A digital image a[m,n] described in a 2D discrete space is derived
from an analog image a(x,y) in a 2D continuous space through a sampling
process that is frequently referred to as digitization. For now we will look at
some basic definitions associated with the digital image. The effect of
digitization is shown in Figure 1.
19
Aditya@poltekom.ac.id
20. DIGITAL IMAGE DEFINITIONS
0,2 nM 3,2 nM
Sample range of colour in reality world is an analog signal
20
Aditya@poltekom.ac.id
21. DIGITAL IMAGE DEFINITIONS
0,2 nM 3,2 nM
The idea of digitization
Is taking sample of a range or an analog value
21
Aditya@poltekom.ac.id
22. DIGITAL IMAGE DEFINITIONS
0,2 nM 3,2 nM
00 01 10 11
2 bit colour representation
The idea of digitization
Is taking sample of a range or an analog value
22
Aditya@poltekom.ac.id
24. DIGITAL IMAGE DEFINITIONS
The 2D continuous image a(x,y) is divided into N
rows and M columns. The intersection of a row and a
column is termed a pixel (pixel comes from “picture element”).
The value assigned to the integer coordinates [m,n] with
{m=0,1,2,…,M–1} and {n=0,1,2,…,N–1} is a[m,n]. In
fact, in most cases a(x,y) which we might consider to be
the physical signal that impinges on the face of a 2D
sensor is actually a function of many variables including
depth (z), color (l), and time (t). Unless otherwise stated,
we will consider the case of 2D, monochromatic, static
images in this chapter.
24
Aditya@poltekom.ac.id
25. DIGITAL IMAGE DEFINITIONS
A pixel contain these information : a (x, y, z, l, t)
a = illumination / light exposure in a certain pixel
X = horizontal coordinate
Y = vertical coordinate
Z = depth
L = colour
T = time frame
25
Aditya@poltekom.ac.id
26. DIGITAL IMAGE DEFINITIONS
A pixel contain these information : a (x, y, z, l, t)
a = illumination / light exposure in a certain pixel High
Light
Low exposure
Light
exposure
26
Aditya@poltekom.ac.id
27. DIGITAL IMAGE DEFINITIONS
A pixel contain these information : a (x, y, z, l, t)
X, Y = 2 dimensional coordinate
Y1 Y2
X1
X2
27
Aditya@poltekom.ac.id
28. DIGITAL IMAGE DEFINITIONS
A pixel contain these information : a (x, y, z, l, t)
Z = depth bottom
surface
28
Aditya@poltekom.ac.id
29. DIGITAL IMAGE DEFINITIONS
A pixel contain these information : a (x, y, z, l, t)
l = colour Yellow
colour
Red
colour
29
Aditya@poltekom.ac.id
30. DIGITAL IMAGE DEFINITIONS
A pixel contain these information : a (x, y, z, l, t)
Picture taken in a different time frame
t = time frame
t1
t2
t3
t4
30
Introduction to Image Processing Aditya@poltekom.ac.id
31. DIGITAL IMAGE DEFINITIONS
The image shown in Figure 1 has been divided into N = 16 rows and
M = 16 columns. The value assigned to every pixel is the average brightness in
the pixel rounded to the nearest integer value. The process of representing
the amplitude of the 2D signal at a given coordinate as an integer value
with L different gray levels is usually referred to as amplitude
quantization or simply quantization.
31
Aditya@poltekom.ac.id
32. COMMON VALUES
There are standard values for the various
parameters encountered in digital image processing.
These values can be caused by video standards, by
algorithmic requirements, or by the desire to keep digital
circuitry simple. Table 1 gives some commonly
encountered values.
32
Aditya@poltekom.ac.id
33. COMMON VALUES
Quite frequently we see cases of M=N=2K where {K =
8,9,10}. This can be motivated by digital circuitry or by
the use of certain algorithms such as the (fast) Fourier
transform.
The number of distinct gray levels is usually a power of
2, that is, L=2B where B is the number of bits in the
binary representation of the brightness levels. When
B>1 we speak of a gray-level image; when B=1 we speak
of a binary image. In a binary image there are just two
gray levels which can be referred to, for example, as
“black” and “white” or “0” and “1”.
33
Aditya@poltekom.ac.id
34. CHARACTERISTIC OF
IMAGE OPERATIONS
There is a variety of ways to classify and characterize image
operations. The reason for doing so is to understand what type of results we
might expect to achieve with a given type of operation or what might be the
computational burden associated with a given operation.
34
Aditya@poltekom.ac.id
35. ADVANTAGES OF IMAGE
PROCESSING
Medical
Sharpen X-Ray result, Analysis of MRI, etc
Technology and Communications
Reduce noise from satellite image, video streaming
Game
Shadow effect on water surface, light effect, etc
Photography and Films
Contrast, brightness, illegal photo manipulations, etc
35
Aditya@poltekom.ac.id