it is a Visible surface detection method is also known as depth buffer method. In this method detect the visible surface by using the distance of the object from the projections plane.
it is a Visible surface detection method is also known as depth buffer method. In this method detect the visible surface by using the distance of the object from the projections plane.
Operations in Digital Image Processing + Convolution by ExampleAhmed Gad
Digital image processing operations can be either point or group.
This presentation explains both operations (point and group) and shows how convolution works by a numerical example.
Ahmed Fawzy Gad
ahmed.fawzy@ci.menofia.edu.eg
Information Technology Department
Faculty of Computers and Information (FCI)
Menoufia University
Egypt
Find me on:
AFCIT
http://www.afcit.xyz
YouTube
https://www.youtube.com/channel/UCuewOYbBXH5gwhfOrQOZOdw
Google Plus
https://plus.google.com/u/0/+AhmedGadIT
SlideShare
https://www.slideshare.net/AhmedGadFCIT
LinkedIn
https://www.linkedin.com/in/ahmedfgad/
ResearchGate
https://www.researchgate.net/profile/Ahmed_Gad13
Academia
https://www.academia.edu/
Google Scholar
https://scholar.google.com.eg/citations?user=r07tjocAAAAJ&hl=en
Mendelay
https://www.mendeley.com/profiles/ahmed-gad12/
ORCID
https://orcid.org/0000-0003-1978-8574
StackOverFlow
http://stackoverflow.com/users/5426539/ahmed-gad
Twitter
https://twitter.com/ahmedfgad
Facebook
https://www.facebook.com/ahmed.f.gadd
Pinterest
https://www.pinterest.com/ahmedfgad/
To highlight the contribution made to the total image appearance by specific bits.i.e. Assuming that each pixel is represented by 8 bits, the image is composed of 8 1-bit planes.Useful for analyzing the relative importance played by each bit of the image.
This is the basic introductory presentation for beginners. It gives you the idea about what is image processing means. The presentation consists of introduction to digital image processing, image enhancement, image filtering, finding an image edge, image analysis, tools for image processing and finally some application of digital image processing.
Operations in Digital Image Processing + Convolution by ExampleAhmed Gad
Digital image processing operations can be either point or group.
This presentation explains both operations (point and group) and shows how convolution works by a numerical example.
Ahmed Fawzy Gad
ahmed.fawzy@ci.menofia.edu.eg
Information Technology Department
Faculty of Computers and Information (FCI)
Menoufia University
Egypt
Find me on:
AFCIT
http://www.afcit.xyz
YouTube
https://www.youtube.com/channel/UCuewOYbBXH5gwhfOrQOZOdw
Google Plus
https://plus.google.com/u/0/+AhmedGadIT
SlideShare
https://www.slideshare.net/AhmedGadFCIT
LinkedIn
https://www.linkedin.com/in/ahmedfgad/
ResearchGate
https://www.researchgate.net/profile/Ahmed_Gad13
Academia
https://www.academia.edu/
Google Scholar
https://scholar.google.com.eg/citations?user=r07tjocAAAAJ&hl=en
Mendelay
https://www.mendeley.com/profiles/ahmed-gad12/
ORCID
https://orcid.org/0000-0003-1978-8574
StackOverFlow
http://stackoverflow.com/users/5426539/ahmed-gad
Twitter
https://twitter.com/ahmedfgad
Facebook
https://www.facebook.com/ahmed.f.gadd
Pinterest
https://www.pinterest.com/ahmedfgad/
To highlight the contribution made to the total image appearance by specific bits.i.e. Assuming that each pixel is represented by 8 bits, the image is composed of 8 1-bit planes.Useful for analyzing the relative importance played by each bit of the image.
This is the basic introductory presentation for beginners. It gives you the idea about what is image processing means. The presentation consists of introduction to digital image processing, image enhancement, image filtering, finding an image edge, image analysis, tools for image processing and finally some application of digital image processing.
Image segmentation techniques
More information on this research can be found in:
Hussein, Rania, Frederic D. McKenzie. “Identifying Ambiguous Prostate Gland Contours from Histology Using Capsule Shape Information and Least Squares Curve Fitting.” The International Journal of Computer Assisted Radiology and Surgery ( IJCARS), Volume 2 Numbers 3-4, pp. 143-150, December 2007.
A usability study was used to measure user performance and user preferences for a CAVETM
immersive stereoscopic virtual environment with wand interfaces compared directly with a workstation nonstereoscopic
traditional CAD interface with keyboard and mouse. In both the CAVETM and the adaptable
technology environments, crystal eye glasses are used to produce a stereoscopic view. An ascension flock of
birds tracking system is used for tracking the user’s head and wand pointing device positions in 3D space.
It is argued that with these immersive technologies, including the use of gestures and hand movements, a more
natural interface in immersive virtual environments is possible. Such an interface allows a more rapid and
efficient set of actions to recognize geometry, interaction within a spatial environment, the ability to find errors,
and navigate through a virtual environment. The wand interface provides a significantly improved means of
interaction. This study quantitatively measures the differences in interaction when compared with traditional
human computer interfaces.
This paper provides analysis via usability study methods for Find and Repair Manipulation termed as
Benchmark 2. During testing, testers are given some time to “play around” with the CAVETM environment for
familiarity before undertaking a specific exercise. The testers are then instructed regarding tasks to be
completed, and are asked to work quickly without sacrificing accuracy. The research team timed each task, and
recorded activity on evaluation sheets for Find and Repair Manipulation Test. At the completion of the testing
scenario involving navigation, the subject/testers were given a survey document and asked to respond by
checking boxes to communicate their subjective opinions.
Design of State Estimator for a Class of Generalized Chaotic Systemsijtsrd
In this paper, a class of generalized chaotic systems is considered and the state observation problem of such a system is investigated. Based on the time domain approach with differential inequality, a simple state estimator for such generalized chaotic systems is developed to guarantee the global exponential stability of the resulting error system. Besides, the guaranteed exponential decay rate can be correctly estimated. Finally, several numerical simulations are given to show the effectiveness of the obtained result. Yeong-Jeu Sun "Design of State Estimator for a Class of Generalized Chaotic Systems" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29270.pdf Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/29270/design-of-state-estimator-for-a-class-of-generalized-chaotic-systems/yeong-jeu-sun
An Exponential Observer Design for a Class of Chaotic Systems with Exponentia...ijtsrd
In this paper, a class of generalized chaotic systems with exponential nonlinearity is studied and the state observation problem of such systems is explored. Using differential inequality with time domain analysis, a practical state observer for such generalized chaotic systems is constructed to ensure the global exponential stability of the resulting error system. Besides, the guaranteed exponential decay rate can be correctly estimated. Finally, several numerical simulations are given to demonstrate the validity, effectiveness, and correctness of the obtained result. Yeong-Jeu Sun "An Exponential Observer Design for a Class of Chaotic Systems with Exponential Nonlinearity" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, URL: https://www.ijtsrd.com/papers/ijtsrd38233.pdf Paper URL : https://www.ijtsrd.com/engineering/electrical-engineering/38233/an-exponential-observer-design-for-a-class-of-chaotic-systems-with-exponential-nonlinearity/yeongjeu-sun
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
2. Connected Component Labeling
Ability to assign different labels to various
disjoint component of an image is called
connected component labeling.
This labeling is a fundamental step in
automated image analysis:
a) Shape
b) Area
c) Boundary
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3. Basic Scanning Method
Scan the image from left to right and top to
bottom.
Assume 4-adjacency.
Let p be a pixel at any step in the scanning
process.
Before p the pixel r and t are scanned.
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4. Labeling Algorithm
This algorithm makes two passes over the image:
1. The first pass to assign temporary labels and
record equivalence classes.
2. The second pass to replace each temporary
label by the smallest label of its equivalence
class.
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5. Steps in First Pass
Conditions to check:
1. Does the pixel to the left (West) have the same value as
the current pixel?
Yes – We are in the same region. Assign the same
label to the current pixel
No – Check next condition
2. Do both pixels to the North and West of the current pixel
have the same value as the current pixel but not the same
label?
Yes –Assign the current pixel the minimum of the
North and West labels, and record their
equivalence relationship
No – Check next condition
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6. Steps in First Pass..
3. Does the pixel to the left (West) have a different
value and the one to the North the same value
as the current pixel?
Yes – Assign the label of the North pixel to
the current pixel
No – Check next condition
4. Do the pixel's North and West neighbors have
different pixel values than current pixel?
Yes – Create a new label id and assign it to
the current pixel
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7. Steps in Second Pass
In the First pass we record some equivalence
relationships.
In Second Pass:
1. Process Equivalence pairs to form
equivalent classes.
2. Re-label the element with the label
assigned to its equivalent classes.
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1 2
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1 1 1 1 (1,2) equivalent
relation
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1 1 1 1 4 3 (3,4) equivalent
relation
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1 1 3
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1 1 3 3
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1 1 3 3
5
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1 1 3 3
5 1 (1,5) equivalent
relation
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1 1 3 3
5 1 3
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5 1 3 3
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1<= 1,2,5
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1<= 1,2,5
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3<= 3,4
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1 1<= 1,2,5
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1
Here we observed that the image contain two distinct class of regions