This document provides an overview of image matching techniques. It defines image matching as geometrically aligning two images so corresponding pixels represent the same scene region. Key aspects covered include detecting invariant local features, describing features in a scale and rotation invariant way using SIFT, and matching features between images. SIFT is highlighted as an extraordinarily robust technique that can handle various geometric and illumination changes. Feature matching is used in many computer vision applications such as image alignment, 3D reconstruction, and object recognition.
At the end of this lesson, you should be able to;
define segmentation.
Describe edge based in segmentation.
describe thresholding and its properties.
apply edge detection and thresholding as segmentation techniques.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Image segmentation is an important image processing step, and it is used everywhere if we want to analyze what is inside the image. Image segmentation, basically provide the meaningful objects of the image.
At the end of this lesson, you should be able to;
define segmentation.
Describe edge based in segmentation.
describe thresholding and its properties.
apply edge detection and thresholding as segmentation techniques.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Image segmentation is an important image processing step, and it is used everywhere if we want to analyze what is inside the image. Image segmentation, basically provide the meaningful objects of the image.
From Experimentation to Production: The Future of WebGLFITC
Presented at FITC Toronto 2017
More info at http://fitc.ca/event/to17/
Hector Arellano, Firstborn
Morgan Villedieu, Firstborn
Overview
You don’t need an advanced degree in graphics engineering to use WebGL as a robust solution in your web design and development. During this talk you will discover how to harness the power of WebGL for real-world application.
Objective
Discover real-world applications for advanced WebGL techniques
Target Audience
Designers or developers excited to conquer the complexity associated with WebGL
Five Things Audience Members Will Learn
Explore the outer limits of physics effects, shaders and experimentation
Understand how these techniques can be applied to transform 3D to 2D shadows and post-processing
Render real-time liquid in WebGL
Use DOM as a texture so you get the power of WebGL without having to worry about a fallback system
Master the basics by utilizing libraries
This presentation will give a simple overview of image classification technique using difference type software focusing on object-based image classification and segmentation.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
4. Definition
• Image matching can be defined as “the process of bringing two
images geometrically into agreement so that corresponding pixels in
the two images correspond to the same physical region of the scene
being imaged
• Image matching problem is accomplished by transforming (e.g.,
translating, rotating, scaling) one of the images in such a way that the
similarity with the other image is maximized in some sense
• The 3D nature of real-world scenarios makes this solution complex to
achieve, specially because images can be taken from arbitrary
viewpoints and in different illumination conditions.
5. Image Matching
• Image matching is a fundamental aspect of many problems in
computer vision, including object and scene recognition, content-
based image retrieval, stereo correspondence, motion tracking,
texture classification and video data mining.
• It is a complex problem, that remains challenging due to partial
occlusions, image deformations, and viewpoint or lighting changes
that may occur across different images
7. Feature Matching
• What stuff in the left image matches with stuff on the right?
• This information is important for for automatic panorama stitching
9. Even Harder Case
NASA Mars Rover images with SIFT feature matches
Figure by Noah Snavely
10. Image Matching Procedure
1. Detection of distinguished regions
2. Local invariant description of these regions
3. Definition of the correspondence space
4. searching of a globally consistent subset of correspondences.
12. Invariant Local Features
1. At an interesting
point, let’s define a
coordinate system
(x,y axis)
2. Use the coordinate
system to pull out a
patch at that point
13. Invariant Local Features
• Algorithm for finding points and representing their patches should produce similar
results even when conditions vary
• Buzzword is “invariance”
– Geometric invariance: translation, rotation, scale
– Photometric invariance: brightness, exposure, …etc.
Feature Descriptors
14. What makes good feature?
• We would like to align by matching local features of these 3 images
• What would be the good local features (ones easy to match)?
15. Local Measure of Uniqueness
Suppose we only consider a small window of pixels
• What defines whether a feature is a good or bad candidate?
• How does the window change when we shift it?
• Shifting the window in any direction causes a big change
“flat” region:
no change in all
directions
“edge”:
no change along
the edge direction
“corner”:
significant change
in all directions
17. Invariance
Suppose we are comparing two images I1 and I2
– I2 may be a transformed version of I1
– What kinds of transformations are we likely to encounter in
practice?
We’d like to find the same features regardless of the
transformation
– This is called transformational invariance
– Most feature methods are designed to be invariant to
• Translation, 2D rotation, scale
– They can usually also handle
• Limited 3D rotations (SIFT works up to about 60 degrees)
• Limited affine transformations (2D rotation, scale, shear)
• Limited illumination/contrast changes
18. How to achieve invariance?
1. Make sure our detector is invariant
– Harris is invariant to translation and rotation
– Scale is trickier
• common approach is to detect features at many scales using a Gaussian pyramid
(e.g., MOPS)
• More sophisticated methods find “the best scale” to represent each feature (e.g.,
SIFT)
2. Design an invariant feature descriptor
– A descriptor captures the information in a region around the
detected feature point
– The simplest descriptor: a square window of pixels
• What’s this invariant to?
– Let’s look at some better approaches…
19. Scale invariant detection
• Suppose we are looking for
corners
• Key idea: find scale that
gives local maximum of f
– f is a local maximum in both
position and scale
– Common definition of f:
Laplacian
(or difference between two
Gaussian filtered images with
different sigmas)
20. Slide from Tinne Tuytelaars
Lindeberg et al, 1996
Slide from Tinne Tuytelaars
Lindeberg et al., 1996
21.
22. Rotation invariance for feature
descriptors
Find dominant orientation of the image patch
• This is given by x+, the eigenvector of H corresponding to +
– + is the larger eigenvalue
• Rotate the patch according to this angle
Figure by Matthew Brown
23. Multiscale Oriented PatcheS
descriptor
Take 40x40 square window
around detected feature
• Scale to 1/5 size (using
prefiltering)
• Rotate to horizontal
• Sample 8x8 square
window centered at
feature
• Intensity normalize the
window by subtracting
the mean, dividing by the
standard deviation in the
window (both window I
and aI+b will match)
8 pixels
26. Scale Invariant Feature
Transform
Basic idea:
• Take 16x16 square window
around detected feature
• Compute edge orientation (angle
of the gradient - 90 ) for each
pixel
• Throw out weak edges
(threshold gradient magnitude)
• Create histogram of surviving
edge orientations
0 2
27. SIFT Descriptor
Full version
• Divide the 16x16 window into a 4x4 grid of cells (2x2 case shown
below)
• Compute an orientation histogram for each cell
• 16 cells * 8 orientations = 128 dimensional descriptor
28. SIFT Properties
Extraordinarily robust matching technique
• Can handle changes in viewpoint
• Up to about 60 degree out of plane rotation
• Can handle significant changes in illumination, sometimes even day
vs. night (next example)
• Fast and efficient—can run in real time
• Lots of code available
http://people.csail.mit.edu/albert/ladypack/wiki/index.php?title=Kno
wn_implementations_of_SIFT
31. Feature Matching
Given a feature in I1, how to find
the best match in I2?
1. Define distance function that
compares two descriptors
2. Test all the features in I2, find the one
with min distance
How to define the difference
between two features f1, f2?
• Simple approach is SSD(f1, f2)
– Sum of square differences between
entries of the two descriptors
– Can give good scores to very
ambiguous (bad) matches
I1
f1
f2
I2
32. Feature Distance
How to define the difference
between two features f1, f2?
• Better approach: ratio
distance = SSD(f1, f2) /
SSD(f1, f2’)
– f2 is best SSD match to f1 in I2
– f2’ is 2nd best SSD match to f1 in
I2
– gives small values for ambiguous
matches
f1
f2
f2’
I1
I2
33. Evaluating the Results
• How can we measure the performance of a feature matcher?
50
75
200
feature distance
34. True/false Positive
The distance threshold affects performance
• True positives = # of detected matches that are correct
– Suppose we want to maximize these—how to choose threshold?
• False positives = # of detected matches that are incorrect
– Suppose we want to minimize these—how to choose threshold?
50
75
200
feature distance
false match
true match
35. Applications
Features are used for:
• Image alignment (e.g., mosaics)
• 3D reconstruction
• Motion tracking
• Object recognition
• Indexing and database retrieval
• Robot navigation
• … etc.
36. Acknowledgment
Some of slides in this PowerPoint presentation are adaptation from
various slides, many thanks to:
1. Deva Ramanan, Department of Computer Science, University of
California at Irvine (http://www.ics.uci.edu/~dramanan/)