Out-of-Frame: Final How-To’s

Today we wrap up the discussion of out-of-frame images.

Yesterday’s post showed how to make a OOF, where the frame was created post-capture in Photoshop. How about a OOF where the frame is actually part of the image capture?

Remember this image? You should since I featured it several days ago. Let’s see how this was done.

Here’s what the table top still life setup looked like when I made this “real OOF” – black backdrop and a real mat (held in place by “helping hands”). Just frame it all in your viewfinder, leaving out the helping hands, and you’re done. For my original purpose (altered image competition) this version would have been an illegal entry since it wasn’t altered.


For my grand finale how about this OOF – it’s a double exposure – to add to the other two approaches shown yesterday and today.

It was made by combining the following two images –

Is that enough? More about framing of every sort than you ever wanted to know….

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Out-of-Frame: A How-To

The past 10 posts have illustrated images that I call out-of-frame (OOF). Today we have a How-To so that you can make your own. Tomorrow a variation on the theme.

How is OOF done? Open up any image editor capable of doing layers (any flavor of Photoshop will do) and follow along.

Step #1 – Select an image that might lend itself to having part of the image OOF. As shown in the previous post’s examples, the portion that extends over the frame can be a single side, two sides – or even all four sides. Depending on what the image might support, it’s your choice (but note – many images do not lend themselves to OOF at all).

This formation of geese will do.

Step #2 – Place a white rectangle on a layer above your original image. This rectangle later will form one of the four sides of your frame (or the photo’s mat if you prefer). Size the overlay to cover what ever you want to extend beyond the frame.

Step #3 – Erase the white where it covers the parts of the original image that you want to appear out of the frame.

Step #4 – Add additional framing (matting). Note that this added portion does not cover the original image. It simply adds a mat around the remaining edges. I’m showing this in two steps (4 & 5) because I find it’s easier this way when using PS’s Re-size Canvas option, but it can be done in a single step if you want.

Step #5 – Complete the “matting”.

Step #6 – Add color and/or texture to give a realistic photo-mat appearance. Also, add a simulated mat “bevel”. These “realism” touches can be as simple or sophisticated as you like (for example, directional shadow lighting on certain sides of the bevel and in the texture).

Step #7 – For a final touch of realism, add shadows appropriate to the OOF element. If you’ve added shadows in your mat texture and bevel from the previous step then you’ll want to ensure that the light direction for these step #7 shadows match.

And that’s it – you’re done.

Background – I developed OOF 10 years ago when I competed and needed an occasional entry for a category called “altered image” (otherwise known as Photoshop-ed).

  • I preferred showing my work more or less as it came from the camera rather than how it looked after undergoing some “artistic filtering” that I wasn’t very good at to begin with. Thus was born OOF.
  • Competition-wise it was a huge success in that I entered one of these on eight separate occasions and each got a ribbon of some sort. I was amused by the number of judges who actually got up from their chair, walked up to within a foot of the print (this was a print competition where OOF is more effective – deceptive – than a projected image), and ran their finger over it.

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Abstract Art and Photography

It happens. Almost a foot of snow from midnight to 6 AM. Another foot is forecast for today. If you’re in a similar situation, or just want some pleasant diversion, here’s a show I did three years ago for a large photo club (the meeting was canceled due to snow).

Followers of this site know that I like abstract photography. It’s not everyone’s cup-of-tea, more of an acquired-taste, but worthwhile exploring for the benefits it will bring to your photography in general. Why else would abstracts be covered on a site called Photography Improvement? 😉

Here’s a multimedia presentation I made for several photography clubs in Feb 2014

Click the image for

A set of three multimedia videos

Slightly OT – What famous artist popularized “selfies” hundreds of years ago?

That, among other interesting tidbits, is revealed in part-1-of-3


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Image Critiquing: A How-To

This is a repost. It’s long, but if you read it & take it to heart I guarantee you will be a better photographer – or you get your money back 😉

Summary – There are lots of ways to critique. Regardless of how you do it – learn to critique. If you don’t know what is & isn’t a good image, how can you hope to ever make one?

I Critique using the “4-C’s”

Do you know how to critique an image? No, not –

WOW! I like that!“.

That’s not a critique. That’s a Flickr comment.

Supportive but not useful if better photography is the ultimate goal.

Even the most well-intentioned critiques can be hard to take – ego’s need to be put aside.

One of the most common reasons given by newbies for not entering club competitions is fear/embarrassment because of criticisms.

A typical image has both good and bad points. Both should be recognized – the good acknowledged and constructive criticism offered for the bad. To be useful, the praise and criticism must be specific, not general – even more specific than

“There’s a problem with the focus”

What & where specifically and why do you think this happened so the maker can avoid the problem in the future

“The background is more in focus than the subject’s eyes. Your focal point was wrong for the shallow depth of field you used.”

Knowing how to critique images is a key step toward becoming a better photographer.

If you don’t know what makes an image good – and bad – how can you hope to make good images?

If you can’t recognize problems when viewing a displayed image, how do expect to see them when looking through your viewfinder?

The most important critique is self-critique of your own images

I use a structured method for critiquing images built around what I call the 4-C’s.

Take a look at this blog’s subtitle at the top of the page

The subtitle is there because I firmly believe that

Mastery of these four elements is key to Photography Improvement.

The 4-C’s

  1. CRAFTSMANSHIP – Using your camera to control exposure, focus and color for a technically perfect image or for the creative image that you want. Key message – putting you in control of the camera & not vice-verse.
  2. COMPOSITION – Making aesthetically pleasing two-dimensional images
  3. CREATIVITY – Making your images YOUR images (and not like everyone else’s) by building on craftsmanship and composition skills
  4. COMMUNICATION – Inserting emotion and feeling into your images. Great artists believed that art sprang from emotion. (A work of art which did not begin in emotion is not art. Paul Cezanne)

The list above is in the order that the C’s should be applied in an a critique.

The list begins with the most basic skills and progresses to the most difficult to master

Good craftsmanship should be a given even for a relative beginner – especially with today’s cameras

Communication on the other hand is very difficult – especially since it’s so viewer dependent

In another sense the list progresses from “objective” criteria through to “subjective”

Craftsmanship elements, color for example, are very objective. Unless the maker is making some artistic statement (see creativity & communication) we all know what color the bride’s skin and gown should be – it’s not a subjective thing.

Communication, on the other hand, is nearly 100% subjective. What “sings” to me may be “nails on a blackboard” to you.

To round out the story, the list is exactly in the opposite order I use when making an image rather than critiquing one.

Making an image begins with Cezanne’s quote – A work of art which did not begin in emotion is not art. If I can see the potential for an image that sings to me, I’m 90% of the way home toward making a good image.

We can’t begin with an everyday scene, craft & compose it in a creative way – and then “glue emotion” to it at the last-minute. It doesn’t happen that way.

Note – “good image” here means one that is good for me. I really don’t care about what others think. Depending on where you are in your photography development journey, you may (or should) care.

Now that I’ve found my singing image, the rest is straight forward. Starting with creativity I try not to make the presentation of my “song” routine & predictable – I want to be creative. My ingredients for creativity are the first 2-C’s (and treating them as the “RULES” of composition and craftsmanship probably won’t get the creative job done – but you do have to know them before you can break them).

The final two steps are relatively easy.

Usually the most difficult composition task is simplifying the image.

Craftsmanship is easy (or it damn well should be else it’s back to the drawing board for you). You HAVE TO reach the point where craftsmanship (using your tools – camera/lens) is instinctive and your camera is an extension of YOU.

If you have to think about it, even for 5 seconds, you’re not ready to be the best photographer you can be. This where practice, practice, practice comes in….

Craftsmanship errors are inexcusable

This is one reason that Craftsmanship comes first in a critique (especially in judging where 75% of all entries must be eliminated; if you can’t do the basics, there’s little reason to go further)

Craftsmanship is essential in terms of making your camera do what your vision requires for this singing image, including bending & breaking rules in the name of creativity

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What Makes an Image Popular?

Yesterday’s post took yet another look at two MIT image-related algorithms. It showed results in the form of a scatter chart. Today’s post translates that chart’s data points from dots to actual photos. What makes an image popular? Who knows. Depends on lots of subjective factors – not to mention the viewing audience. Shoot for yourself!

Yesterday’s post featured this chart

It included one example photo for each quadrant. Today’s post shows all 68 photos.

xls pop-vs-mem chart

4 quadrant images

Click on the above image for full screen (once doing that you may have to reduce it to fit your screen, “Ctrl -“ on a PC). Within each quad, the most popular image is at the top left and the least is at the bottom right.

Memorable, quads 2 & 3, vs. not as predicted by the MIT algorithm, is heavily biased by whether the image is a landscape or not.

  • See this by comparing the number of landscapes on the left vs. right sides

What makes an image popular is less obvious. Especially since the MIT algorithm considered not only an image’s visual characteristics but, equally or more important, the social context in which it was viewed and by whom (in this case Flickr). Since I don’t shoot for a Flickr (WOW!!!!) audience, I’m not surprised that the MIT program and I don’t agree on a lot of its scores. That doesn’t say that either of us is right or wrong, just that we have different standards.

  • Can anyone hazard an opinion as to what may separate images in the top half from those in the bottom.

This is what happens when you give an engineer a camera 😉

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Image Popularity – An Analysis

For the past week or so I’ve tested two MIT image-related algorithms – one that predicts image memorability and one popularity. I was curious whether there was any correlation between the two. Here’s a chart with some preliminary results.

The tests were done on a sample of my photographs as described here

  • Tested were 68 of ~1800 images I posted daily over a five-year period
    • These 68 each got the most views in the month they were posted
  • Each image was “scored” by the MIT algorithms
    • A plot of the results is shown here
    • Note: the Views axis is for normalized views (actual was many times this)

xls pop-vs-mem chart

Some observations:

  • The Chart is divided into four quadrants separated by the median values (50% above & below) for memorability (green vertical line) and views (red horizontal)
    • Images in quads 2 & 4 support the thesis that memorability implies popularity; Quad 1 & 3 images suggest the opposite
    • An actual example image from each quadrant is shown for illustration
  • The broken red trend line shows that, in general, more memorable leads to more popular – but I wouldn’t take that to the bank.

An interesting exercise that yielded no surprises. If I were still exhibiting and competing, I’d still go with what “sings to me” (and to the likely audience; Instagram & Flickr viewers have standards that are way different from exhibit jurors and competition judges). My motto has always been – Shoot For Yourself!

This is what happens when you give an engineer a camera 😉

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Park Your Horse & Buggy Here

As mentioned over the past several months, I moved last summer. Did I mention that I now live in the middle of Amish country – with an emphasis on country?

In the U.S., reserved parking for the handicapped is a law.

How about a horse and buggy?

Seen in a local parking lot. Not law, courtesy (of Costco).

645 PRO Mk III for Apple iPhone 6 Plus_160107_101821_IMG_2588-1

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