Slides from my wildly popular presentation at HP World 2005. Who knew? Grossly over-simplified signal processing methodology and sample photos of models in bikinis was a winning combo, even in San Francisco.
The increasing popularity of animes makes it vulnerable to unwanted usages like copyright violations and
pornography. That’s why, we need to develop a method to detect and recognize animation characters. Skin
detection is one of the most important steps in this way. Though there are some methods to detect human
skin color, but those methods do not work properly for anime characters. Anime skin varies greatly from
human skin in color, texture, tone and in different kinds of lighting. They also vary greatly among
themselves. Moreover, many other things (for example leather, shirt, hair etc.), which are not skin, can
have color similar to skin. In this paper, we have proposed three methods that can identify an anime
character’s skin more successfully as compared with Kovac, Swift, Saleh and Osman methods, which are
primarily designed for human skin detection. Our methods are based on RGB values and their comparative
relations.
The increasing popularity of animes makes it vulnerable to unwanted usages like copyright violations and pornography. That’s why, we need to develop a method to detect and recognize animation characters. Skin detection is one of the most important steps in this way. Though there are some methods to detect human skin color, but those methods do not work properly for anime characters. Anime skin varies greatly from human skin in color, texture, tone and in different kinds of lighting. They also vary greatly among themselves. Moreover, many other things (for example leather, shirt, hair etc.), which are not skin, can have color similar to skin. In this paper, we have proposed three methods that can identify an anime character’s skin more successfully as compared with Kovac, Swift, Saleh and Osman methods, which are primarily designed for human skin detection. Our methods are based on RGB values and their comparative relations.
ICCASP Human Skin Detection using RGB, HSV and YCbCr Color ModelsChaitanya Bapat
As part of International Conference on Communication and Signal Processing (ICCASP) at Dr. Babasaheb Ambedkar Technological University (BATU), Lonere, India. Paper presentation about a combinatorial approach towards skin detection
The increasing popularity of animes makes it vulnerable to unwanted usages like copyright violations and
pornography. That’s why, we need to develop a method to detect and recognize animation characters. Skin
detection is one of the most important steps in this way. Though there are some methods to detect human
skin color, but those methods do not work properly for anime characters. Anime skin varies greatly from
human skin in color, texture, tone and in different kinds of lighting. They also vary greatly among
themselves. Moreover, many other things (for example leather, shirt, hair etc.), which are not skin, can
have color similar to skin. In this paper, we have proposed three methods that can identify an anime
character’s skin more successfully as compared with Kovac, Swift, Saleh and Osman methods, which are
primarily designed for human skin detection. Our methods are based on RGB values and their comparative
relations.
The increasing popularity of animes makes it vulnerable to unwanted usages like copyright violations and pornography. That’s why, we need to develop a method to detect and recognize animation characters. Skin detection is one of the most important steps in this way. Though there are some methods to detect human skin color, but those methods do not work properly for anime characters. Anime skin varies greatly from human skin in color, texture, tone and in different kinds of lighting. They also vary greatly among themselves. Moreover, many other things (for example leather, shirt, hair etc.), which are not skin, can have color similar to skin. In this paper, we have proposed three methods that can identify an anime character’s skin more successfully as compared with Kovac, Swift, Saleh and Osman methods, which are primarily designed for human skin detection. Our methods are based on RGB values and their comparative relations.
ICCASP Human Skin Detection using RGB, HSV and YCbCr Color ModelsChaitanya Bapat
As part of International Conference on Communication and Signal Processing (ICCASP) at Dr. Babasaheb Ambedkar Technological University (BATU), Lonere, India. Paper presentation about a combinatorial approach towards skin detection
Want to make your own pixel art? Cory Martin will share everything you need to know to get started! Learn what differentiates pixel art from other art-forms; get familiar with the various techniques used by pixel artists; and discover the most common mistakes people make when starting out, and how to avoid them.
---
This was for a talk I gave for the Nashville Game Developers group on March 26th, 2018.
Lecture 2: Data, pre-processing and post-processing
Chapters 2,3 from the book “Introduction to Data Mining” by Tan, Steinbach, Kumar.
Chapter 1 from the book Mining Massive Datasets by Anand Rajaraman and Jeff Ullman
The TCP/IP protocol system is used by virtually every modern data network to quickly and reliably move data from node to node. This presentation covers what TCP/IP is, what it does, it’s most important features, and how it was developed.
This presentation explores the reasons why software projects are significantly more difficult to manage than other types of projects. Software-specific issues related to scope, resources, and time are explored, as well as how software projects differ from other projects in the physical world. An argument for why software constitutes a “Wicked Problem” is expanded, and numerous software development myths are attacked with real-world anecdotes and solutions.
Pricing Analytics: Segmenting Customers To Maximize RevenueMichael Lamont
Potential customers for a product or service can be segmented into valuation groups. High valuation groups are willing to pay more for the product or service, while low valuation groups are only willing to pay a lesser amount for the same product or service. This presentation provides a basic background on yield management through customer segmentation, and a hands-on example of modeling airline customer segmentation using Excel.
Want to make your own pixel art? Cory Martin will share everything you need to know to get started! Learn what differentiates pixel art from other art-forms; get familiar with the various techniques used by pixel artists; and discover the most common mistakes people make when starting out, and how to avoid them.
---
This was for a talk I gave for the Nashville Game Developers group on March 26th, 2018.
Lecture 2: Data, pre-processing and post-processing
Chapters 2,3 from the book “Introduction to Data Mining” by Tan, Steinbach, Kumar.
Chapter 1 from the book Mining Massive Datasets by Anand Rajaraman and Jeff Ullman
The TCP/IP protocol system is used by virtually every modern data network to quickly and reliably move data from node to node. This presentation covers what TCP/IP is, what it does, it’s most important features, and how it was developed.
This presentation explores the reasons why software projects are significantly more difficult to manage than other types of projects. Software-specific issues related to scope, resources, and time are explored, as well as how software projects differ from other projects in the physical world. An argument for why software constitutes a “Wicked Problem” is expanded, and numerous software development myths are attacked with real-world anecdotes and solutions.
Pricing Analytics: Segmenting Customers To Maximize RevenueMichael Lamont
Potential customers for a product or service can be segmented into valuation groups. High valuation groups are willing to pay more for the product or service, while low valuation groups are only willing to pay a lesser amount for the same product or service. This presentation provides a basic background on yield management through customer segmentation, and a hands-on example of modeling airline customer segmentation using Excel.
Sales and promotional discounts let retailers reach pools of customers that value the same product differently. Modeling the pool of potential buyers, and how it changes over time, lets you optimize how and when sales and discounts are applies. This presentation provides a hands-on demonstration of modeling the pool of potential buyers, and using Excel’s Solver tool to optimize revenue from that shopper pool by manipulating price.
The prices of several product classes – notably fashion and technology – tend to drop over time. One possible reason for the drop over time is different customers assigning a different value to the same product or service. Price skimming models can be used to maximize a product or service’s revenue by planning price reductions over time in a manner that slowly cuts tranches of higher-value customers out of the market. This presentation provides a hands-on demonstration of constructing a price skimming model in Excel, and optimizing planned price reductions.
Pricing Analytics: Estimating Demand Curves Without Price ElasticityMichael Lamont
Most techniques used to created demand curves depend on the product’s price elasticity. But what if you don’t have or can’t obtain the price elasticity figures for a particular product? If you can make reasonable estimates of demand for a product at a high, median, and low price point, then you can still construct a reasonable estimate of the demand curve over the range of those prices. This presentation shows how to use Excel’s line fitting and Solver functionality to construct a demand curve without knowing the product’s price elasticity, and determine the optimal price for the product that maximizes profit margin.
Business Intelligence: Multidimensional AnalysisMichael Lamont
An introduction to multidimensional business intelligence and OnLine Analytical Processing (OLAP) suitable for both a technical and non-technical audience. Covers dimensions, attributes, measures, Key Performance Indicators (KPIs), aggregates, hierarchies, and data cubes.
The “best” price for a product or service is one that maximizes profits, not necessarily the price that sells the most units. This presentation uses real-world examples to explore how Excel’s Solver functionality can be used to calculate the optimal price for any product or service.
Pricing Analytics: Creating Linear & Power Demand CurvesMichael Lamont
An introduction to the two most common types of demand curves (linear and power), which can be used to estimate the price for a product or service that maximizes profit margins. Includes hands-on real-world examples using Excel.
HP Tech Forum 2009 presentation covering some of the ways spammers harvest email addresses on the Internet (and how you can prevent it), including an in-depth look at three commonly used software packages.
Evaluating and Implementing Anti-Spam SolutionsMichael Lamont
Presentation from HP World 2004 that explores common anti-spam technologies including how they work, how effective they are, their relative strengths/weaknesses, and how spammers try to circumvent them. Also has a section on evaluating anti-spam software packages.
Methodology for a technical evaluation of software-based spam filters - a hot topic back in 2005. It was originally going to be given at the HP Tech Forum in New Orleans in Sept 2005 - Katrina forced the conference to cancel while I was literally on the way to the Boston airport. Ended up giving this presentation at the rescheduled conference in Orlando in Oct 2005.
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
A Comprehensive Look at Generative AI in Retail App Testing.pdfkalichargn70th171
Traditional software testing methods are being challenged in retail, where customer expectations and technological advancements continually shape the landscape. Enter generative AI—a transformative subset of artificial intelligence technologies poised to revolutionize software testing.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
✅With one keyword, generate complete funnels, websites, landing pages, and more.
✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
✅99.99% Up-Time Guaranteed
✅30 Days Money-Back Guarantee
✅ZERO Upfront Cost
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
Into the Box Keynote Day 2: Unveiling amazing updates and announcements for modern CFML developers! Get ready for exciting releases and updates on Ortus tools and products. Stay tuned for cutting-edge innovations designed to boost your productivity.
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
SOCRadar Research Team: Latest Activities of IntelBrokerSOCRadar
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
Enhancing Project Management Efficiency_ Leveraging AI Tools like ChatGPT.pdfJay Das
With the advent of artificial intelligence or AI tools, project management processes are undergoing a transformative shift. By using tools like ChatGPT, and Bard organizations can empower their leaders and managers to plan, execute, and monitor projects more effectively.
2. Overview
• Role of image filtering in anti-spam
filtering
• Two popular image filtering methods:
– Shape recognition
– Skin detection
• Example image filtering
• Image filtering issues
• Tools you can play with on your own
3. What Isn’t Covered
• Anything requiring advanced math
• Optical character recognition (OCR)
4. Spam Images
• A picture is worth 1000 words…
• …and it’s a lot harder to filter than
1000 words.
• Especially when spamvertizing
pornography, photos are essential
marketing tools.
5. Spam Images
• Right now, a spam filter can be very
effective without looking at images.
• This is going to change when the
majority of sites start installing more
accurate filters, and spammers are
forced to adapt.
6. 90-Second Image Review
• To understand how image filtering
technologies work, you need a basic
understanding of how computers
represent images.
• Images are broken into square dots,
which correspond to pixels on a
monitor.
8. 90-Second Image Review
• Each dot’s color is represented by 3
components: red, green, and blue.
• Each of the three color components
has a value of 0 to 255.
• If all three are 0, then the pixel is black.
If all three are 255, then the pixel is
white.
9. 90-Second Image Review
• The higher the number, the more
intense the color component.
• Example: Increasing red value from 0
to 255 while leaving other components
at 0:
10. Shape Recognition
• Identifies objects in an image using
posterization and edge finding.
• Extracts interesting objects and
searches for similar objects in a
database of “bad” objects.
• For our application, the objects are
human body parts.
11. Posterization
• Dramatically reduces the number of
colors in an image.
• Has the side effect of lumping most of
an object’s pixels together.
• Called “posterization” because the
same kind of color reduction used to
be done for images printed on posters.
14. Posterization - Method
• A number of color bins are created.
• The number of bins is a lot less than
the ~16m colors that are possible.
• Each bin holds several hundred colors
that are closely related.
• Every color in the bin is represented by
the average color.
15. Posterization - Method
• Example: If a bin contained every
shade of red from light pink to dark
blood, every color in the bin would be
represented by plain old red.
• The posterization process itself
consists of replacing the color of every
pixel in the image with its bin’s
representative color.
20. Edge Finding
• After posterizing the image, edge
finding is used to identify individual
objects.
• Edge finding determines the
boundaries between different patches
of color and contrast.
23. Edge Finding - Method
• The edge finding program scans the
image looking for pixels that are very
different from their neighbors.
• When it finds a radically different pixel,
it marks it as part of an edge.
• Good edge finding algorithms look at
lots of neighboring pixels to help
reduce noise.
29. Object Extraction
• Once objects have been identified with
posterization and edge finding, they’re
easy to extract.
30. Object Extraction
• Leg, midriff, and upper torso objects
are being searched in the case of
people wearing swimsuits.
31. Object Extraction
• A database of known objects is
searched for matches to the extracted
objects.
• Both object shape and color are used
in the search.
• Comparisons are done with a fuzzy
logic algorithm, since it’s unlikely two
objects will be exactly alike.
32. Skin Detection
• Subset of an image classification
method called color histogram
matching.
• Finds patches of skin tone in an image.
• Calculates the overall percentage of
the image that is skin.
• If more than a specified amount of the
image is skin, it’s filtered.
33. Skin Tones
• Almost all human skin is the same hue
- saturation differences result in
different skin colors.
• Human skin tones don’t often appear
in other photographed objects, so color
alone can be used to identify skin.
• Skin tones are primarily red, without
any blue and little if any green.
34. Skin Color Model
• To identify skin tones in an image, a
filter needs to know what colors are
skin tones.
• You could hardcode every skin color,
but there are tens of thousands of
them.
• Much more accurate to identify skin
patches in an image and “train” the
filter.
35. Skin Color Training
• Works almost like Bayesian filter
training, but with image colors instead
of message tokens.
• Filter maintains one database of skin
colors, and another database of non-
skin colors.
• If a color appears more often in the
skin color database, it’s treated as a
skin color.
36. Skin Color Training
• This system has the nice side-effect of
dropping out most skin colors that also
appear in non-skin areas of photos.
38. Skin Identification
• To analyze an image, the filter
examines the color of each pixel.
• If the color is a skin tone, the filter
marks the pixel as skin.
• When every pixel has been examined,
the % of the image that is skin is
calculated.
• If the % is over a specified threshold,
the image is filtered.
71. Shape Recognition Problems
• Following are examples of images that
shape recognition doesn’t handle
correctly.
• Skin detection handles them correctly,
but only because it’s biased to filter
images with a lot of skin.
97. Skin Detection Problems
• Following are examples of images that
skin detection incorrectly filters.
• Shape recognition works for most of
these, mainly because it can’t extract
any useful shapes.
115. Wedding Photos
• Wedding photos are guaranteed to
make a mess of image filters.
• Skin fades into the background
because of soft lighting, soft filters, and
retouching.
• Turns out that brides get upset if the
image is crystal clear with good
contrast - it shows off skin flaws.
116. Wedding Photos
• Skin detection filters start identifying
everything as skin (false positive).
• Shape recognition filters give up and
don’t filter the message (accurate, but
not for the right reasons).
• Porn tends not to be shot with soft
lighting - good contrast makes skin
“pop” in photos.
127. “Art Porn”
• Usually shot with the same lighting
effects as wedding photos.
• Rarely seen in email.
• In this case, skin detection is accurate
for the wrong reasons while shape
recognition lets the image pass.
133. Things I Can’t Show You
• S & M
– Skin tends to be covered with “clothing”
– Shapes are broken up by all of the
paraphernalia
• Simpson’s shocker
• Still images from “interesting” videos
– Images are badly pixelated
– Colors are muddy and smudged
134. Image Filtering Issues
• Accuracy:
– Shape recognition misses lots of images it
shouldn’t (false negatives)
– Skin detection filters lots of images it
shouldn’t (false positives)
– Best skin detection systems are about
80% accurate
– Best shape recognition systems are about
40% accurate
135. Image Filtering Issues
• Performance:
– Image filtering requires huge amounts of
memory, CPU time, and disk bandwidth.
– Unacceptably slows down most site’s
email servers/filtering systems.
– DL380 benchmark:
• ~1.2 million messages/hour with no filtering
• ~195,000 messages/hour with skin detection
• ~69,000 messages/hour with shape recognition
136. Image Filtering Issues
• Diminishing returns on accuracy - most
spam filters won’t see a noticeable
increase in accuracy with the addition
of image filtering.
• That’s likely to change in the future as
spammers discover it’s one of the
better options for circumventing current
solutions.
137. I Wanna Play!
• Shape recognition:
– UC Berkeley’s blobworld
• Open source
• http://elib.cs.berkeley.edu/
– Skin detection
• No good open-source examples
• Trivial to write your own using ImageMagick
• http://www.imagemagick.org/
138. Quick Review
• We covered:
– How and why images appear in spam
– Why the use of images in spam is likely to
increase
– Two methods for filtering images
– Examples of how the two methods work
and don’t work
– Why image filtering isn’t widely used at
this point.