How nature outsmarts your Smartphone

There is no doubt that modern technology is getting smarter, smaller and cheaper all of the time, and the modern smartphone is to the fore in how most humans (that own one) access these advancements in technology.

However, it’s also refreshing (and a reassuring in a strange kind of way) to know that such humble and innate everyday objects, found in the most non-technical and un-advanced parts of our world, can still outsmart us all!

The Joint Photographic Experts Group – JPEG

A significant majority of modern smartphones (and digital cameras) use the JPEG image file format to store the photographs taken by the device. This file format is named after the Joint Photographic Experts Group, which published the first version of the specification in 1992.

The file format was famed for introducing 3 main features:

  1. The possibility of more than 16 million different colours for each pixel in the image.
  2. Varying levels of image compression, reducing the size of the files and making them ideal for use on websites.
  3. An ability to store additional meta data (known as Exif data) inside the image file (e.g. date, time, location, shutter speed).

Digital Compression

By recognising repeating patterns of colour within an image, the JPEG compression algorithms are able to reduce the size of the file containing that image, usually without any significant (or noticeable) loss in image quality. However, with the ever-increasing storage capacity of smartphones, digital cameras, memory sticks and computer hard drives, how many of us ever really take any notice of the size of image files that we are dealing with?

Nature’s Patterns

As it happens, I did just this on foot of a recent family occasion in our back garden where I took rather a lot of photographs featuring grass (plus family members, of course). While syncing the photos to my computer later that evening, I noticed that it was taking much longer than usual so took a closer look when the transfer was complete.

What I discovered then lead me to take a number of other photos of nature scenes the following day, underpinning my theory that nature was clearly outsmarting my smartphone in a variety of very interesting (and surprising ways). Here is what I found.

The Evidence

Each of the following photos were taken using the same smartphone, using the same unmodified Camera app, over the course of 2 days. For the most part, they are shown in order of size (smallest to largest) with some exceptions along the way.

Part Ocean, Part Sky, Part Rocks – 1.5MB

Clearly, the proliferation of grey/dark colours here has lead to a very high level of compression, resulting in a much smaller file.

Very Cloudy Sky – 2.4MB

This very consistent pattern of grey yielded a very high compression rate also, but with perhaps with slightly less dark colours causing a marginal increase in file size.

Semi Clear Sky – 2.6MB

Surprisingly, this quite different skyline (with a lot more blue) was only marginally larger than the very cloudy scene above, but it still compressed very well due to the consistency of regions of blue, grey and white throughout.

Part Sky, Part Ocean on a Grey Day – 3.4MB

With around 60% of this shot featuring some random sea waves, the level of compression achieved is slightly less than others.

Rippled Water – 4.2MB

While featuring a mostly blue/green hue, the degree of randomness to the ripples prevented a higher level of compression here.

Beach Stones – 5.2MB

So now it begins to get interesting, with nature fighting back. This scene features a large selection of pebbles and stones, of differing shapes, sizes, colours and orientation. Overall, quite a random scene which is duly borne out in the largest file size so far.

Plant Leaves – 5.3MB

There’s quite lot of the same shade of green in this shot, which should yield good compression, but the random shape, size and orientation of the leaves is clearly confusing the compression algorithm, resulting in a larger than expected file.

Cliff Rock Closeup – 5.7MB

Large rocks are normally quite uniform in their colour but a couple of thousand years of being battered by the elements is bound to introduce some character in the form of random edges, wear & tear as well as other inclusions, all reducing the amount of compression the camera was able to achieve.

Forest Ferns – 6.6MB

This scene features predominantly green elements of generally the same shade. However, the size, orientation and varying shape of the leaves and branches across the full spectrum of the shot result in a very confused (and highly random) panorama for the camera.

Regular Garden Grass Closeup – 7.2MB

Surprisingly, the most ordinary patch of grass (somewhat close up) causes the most havoc and lowest level of compression for our camera, with the utter chaos that is the size, shape, length, colour, orientation and depth of the blades of grass resulting in the largest file size. The camera even struggled to retain it’s focus in the outer regions of the shot (see top left), further proving that nature always has the upper hand.

Pebble Dashed Wall – 6.2MB

For good measure, I also sampled this man-made creation with a reasonably high degree of randomness. While the colour and dispersal of the pebbles was most definitely random, the camera did still manage some level of compression, most likely based on the consistent colour of the background cement.


The level of scientific analysis conducted during this impromptu experiment was minimal at best and no pixels were harmed during the gathering of evidence herein. But you’d be amazed what other surprises mother nature is likely to throw up so get out there and discover your own flavour of randomness!

A case for more Open Source at Apple

Open Source Context

I’ve been involved in the software industry for almost 30 years and have long been an admirer of open source software, both in terms of what it stands for and in terms of the inherent value it provides to the communities that create it and support it.

I’m even old enough to remember reading about the creation of the Free Software Foundation itself by Richard Stallman in 1985 and couldn’t be happier to now find myself working at the king pins of open source, Red Hat (through the acquisition of FeedHenry in 2014).

And while in recent years it’s been reassuring to see more and more other companies adopt an open source strategy for some of their products, including the likes of Apple and Microsoft, it’s been equally soul destroying having to live with the continued closed source nature of some of their other products. Take Apple’s Photos app for iOS as a case in point.

Apple iPhoto

Some time around 2011, I took the decision to switch to Apple’s excellent iPhoto app for managing my personal photo collection, principally due the facial recognition and geolocation features but also because of the exceptional and seamless user experience across the multitude of Apple devices I was amassing.

Then, in late 2012, I undertook a very lengthly personal project (spanning 9 months or more) to convert my extended family’s vintage photo collection to digital format, importing them to iPhoto and going the extra mile to complete the facial and location tagging also.

The resultant experience was incredible, particularly when synced onto my iPad of the time (running iOS 6). Hours at a time were spent perusing through the memories it invoked, with brief interludes of tears and laughter along the way. What was particularly astonishing was how the older generations embraced the iPad experience within minutes of holding the device for the very first time. This was the very essence of what Steve Jobs worked his entire life for, and for this I am eternally grateful to the genius he clearly was.

Apple Photos

However, since then, with the launch of subsequent releases of iOS I have never been able to recreate the same experience, for two reasons.

Firstly, the user interface of the iPhoto app kept changing (becoming less intuitive each time, proven by the lessening magic experienced by the same generation that previously loved it so much), and secondly, it was replaced by the Photos app outright which, incredibly, has one simple but quite incredulous bug – it cannot sort!

Yes, quite incredibly, the Photos app for iOS cannot sort my photos when using the Faces view. If you don’t believe me, just Google phrase “apple photos app sort faces” and take your pick of the articles lamenting such a rudimentary failing.

A Case for Open Source

So what does this have to with open source?“, I hear you ask.

Well, trawling through the countless support articles on Apple’s user forums, it seems that this bug has been confirmed by hundreds of users but, several years later, it is still not fixed. If this was an open source project, it would have been long since fixed by any one of a number of members of the community I’m sure would form around it, and potentially even by me!

So c’mon Apple, let’s have some more open source and let’s make your products better, together.

Injecting Data into Scanned Vintage Photos

In a previous post, entitled Vintage Photo Scanning – A Journey of Discovery, I shared my experiences while digitising my parent’s entire vintage photo collection.

As part of that pet project, I also took the liberty of digitally injecting some of the precious data I had learned about them (i.e. when and where the photos were taken, and who was in them) into the photo files themselves, so that it would be preserved forever along with the photo is pertained to. This article explains how I did that.

Quick Recap

My starting point was a collection of around 750 digital images, arranged into a series of folders and subdirectories, and named in accordance with the following convention:


So the task at hand was how to programmatically (and thus, automatically) inject data into each of these files, starting over if required, so that sorting them or importing them into photo management software later becomes much easier.

Ready, Steady, Bash!

In order to process many files at a time, you’re going to need to do a little programming. My favourite language for this sort of stuff is Bash, so expect to see plenty of snippets written in Bash from here on. I am also going to assume that you are running this on a Unix/Linux-based system (sorry, Mr. Gates).


While each photo will have a different date, title, list of people and location, there are some other pieces of data you like to store within them (while you’re at it), which you (or your grandchildren) may be glad of later on. To this end, let’s set up some assumptions and common fields.

Default Data

If you only know the year of a photo, you’ll need to make some assumptions about the month and day:


Reusable File Locations

Define the location of exiftool utility or any other programs you’re using (if they are located in a non-standard part of your system), along with any other temporary files you’ll be creating:

CSVFILE=$(dirname "$0")/photos.csv
GPSFILE=$(dirname "$0")/gps.txt
GPS_COORDS=$(dirname "$0")/gps-coords.txt

Common Metadata

Most photo files support other types of metadata including the make/model of camera used, the applicable copyright statement and of the owner of the files. If you wish to use these, you could define their values in some variables that can be used (for each file) later on:

EXIF_MODEL="HP Deskjet M4500"
EXIF_COPYRIGHT="Copyright (c) 2014, James Mernin"
EXIF_OWNER="James Mernin"

Data Injection

List, Iterate & Extract

Firstly, compile a list of the files you wish to process:

find "$IMAGE_DIR" -name "*.jpg" > $PHOTO_FILES

Now iterate over that list, processing one file at a time:

while read line; do
 # See below for what to do...
done < "$PHOTO_FILES"

Now split the input line to extract the 4 field of data:

BASENAME=`basename "$line" .jpg`
ID_DATE=`echo $BASENAME|cut -d"~" -f1`
ID_TITLE=`echo $BASENAME|cut -d"~" -f2`
ID_PEOPLE=`echo $BASENAME|cut -d"~" -f3`
ID_LOCATION=`echo $BASENAME|cut -d"~" -f4`

Prepare Date & Title

Prepare a suitable value for Year, Month and Day (taking into account the month and day maybe unknown):

DATE_Y=`echo $ID_DATE|cut -d"-" -f1`
DATE_M=`echo $ID_DATE|cut -d"-" -f2`
if [ -z "$DATE_M" ] || [ "$DATE_M" = "$DATE_Y" ]; then DATE_M=$DEFAULT_MONTH; fi
DATE_D=`echo $ID_DATE|cut -d"-" -f3`
if [ -z "$DATE_D" ] || [ "$DATE_D" = "$DATE_Y" ]; then DATE_D=$DEFAULT_DAY; fi

It’s possible the title of some photos may contain a numbered prefix in order to separate multiple photos taken at the same event (e.g. 01-School Concert, 02-School Concert). This can be handled as follows:

TITLE_ORDER=`echo $ID_TITLE|cut -d"-" -f1`
if [ -n "$TITLE_ORDER" ]; then
 if [ $TITLE_ORDER -eq $TITLE_ORDER ] 2>/dev/null; then TITLE=`echo $ID_TITLE|cut -d"-" -f2-`; fi

Location Processing

This is a somewhat complex process but essential boils down to trying to determine the GPS coordinates for the location of each photo. This is because most photo file only support the GPS coordinates inside their metadata. I have used the Google Maps APIs for this step with an assumption that you get an exact match first time. You can, of course, complete this step as a separate exercise beforehand and store the results of that in a separate file to be used as input here.

In any case, the following snippet will attempt to fetch the GPS coordinates for the location of the given photo. Pardon also the crude use of Python for post-processing of the JSON data returned by the Google Maps APIs.

ENCODED_LOCATION=`python -c "import urllib; print urllib.quote(\"$ID_LOCATION\");"`
GPSDATA=`curl -s "$ENCODED_LOCATION&sensor=false"`
NUM_RESULTS=`echo $GPSDATA|python -c "import json; import sys; data=json.load(sys.stdin); print len(data['results'])"`
if [ $NUM_RESULTS -eq 0 ]; then
 GPS_LAT=`echo $GPSDATA|python -c "import json; import sys; data=json.load(sys.stdin); print data['results'][0]['geometry']['location']['lat']"`
 GPS_LNG=`echo $GPSDATA|python -c "import json; import sys; data=json.load(sys.stdin); print data['results'][0]['geometry']['location']['lng']"`

Convert any negative Latitude and Longitude values to North/South or West/East so that your coordinates end up in the correct hemisphere and on the correct side Greenwich, London:

if [ "`echo $GPS_LAT|cut -c1`" = "-" ]; then GPS_LAT_REF=South; else GPS_LAT_REF=North; fi
if [ "`echo $GPS_LNG|cut -c1`" = "-" ]; then GPS_LNG_REF=West; else GPS_LNG_REF=East; fi

Inject Data

You now have all the data you need to prepare the exiftool command:

EXIF_DATE="${DATE_Y}:${DATE_M}:${DATE_D} 12:00:00"
echo "Title: $TITLE" > $PHOTO_DESC
echo "People: $ID_PEOPLE" >> $PHOTO_DESC
echo "Location: $ID_LOCATION" >> $PHOTO_DESC

if [ -n "$ID_LOCATION" ]; then
 $EXIFTOOL -overwrite_original \
  -Make="$EXIF_MAKE" -Model="$EXIF_MODEL" -Credit="$EXIF_CREDIT" -Copyright="$EXIF_COPYRIGHT" -Owner="$EXIF_OWNER" \
  -FileSource="Reflection Print Scanner" -Title="$TITLE" -XMP-iptcExt:PersonInImage="$ID_PEOPLE" "-Description<=$PHOTO_DESC" \
  -AllDates="$EXIF_DATE" -DateTimeOriginal="$EXIF_DATE" -FileModifyDate="$EXIF_DATE" \
  -GPSLatitude=$GPS_LAT -GPSLongitude=$GPS_LNG -GPSLatitudeRef=$GPS_LAT_REF -GPSLongitudeRef=$GPS_LNG_REF \
  $EXIFTOOL -overwrite_original \
   -Make="$EXIF_MAKE" -Model="$EXIF_MODEL" -Credit="$EXIF_CREDIT" -Copyright="$EXIF_COPYRIGHT" -Owner="$EXIF_OWNER" \
   -FileSource="Reflection Print Scanner" -Title="$TITLE" -XMP-iptcExt:PersonInImage="$ID_PEOPLE" "-Description<=$PHOTO_DESC" \
   -AllDates="$EXIF_DATE" -DateTimeOriginal="$EXIF_DATE" -FileModifyDate="$EXIF_DATE" \

Cross your fingers and hope for the best!

Apple iPhoto Integration

Personally, I manage my portfolio of personal photographs using Apple iPhoto so I wanted to import these scanned photos there too. And so the Data Injection measures above I took above simplified this process greatly (especially the Date and Location fields which iPhoto understands natively).

While I did then go on to use iPhoto’s facial recognition features and manually tag each of the people in the photographs (adding several weeks to my project), the metadata injected into the files helped make this a lot easier (as it was visible in the information panel displayed beside each photo) in iPhoto.

Return on Investment


In all, this entire project took almost 9 months to complete (with an investment of 2-3 hours per evening, 1-2 nights per week). The oldest photograph I scanned was from 1927 and the most precious one was one from my early childhood holding a teddy bear that my own children now play with.


The total number of photos processed was somewhere in the region of 750. And while that may appear to be a very long time for relatively few photographs, the return on investment is likely to last for many, many multiples of that time.

Upon Reflection

I’ve also been asked a few times since then, “Would I do it again?”, to which the answer is an emphatic “Yes!” as the rewards will last far longer than I could ever have spent doing the work.

However, when asked, “Could I do it again for someone else?”, that has to be a “No”. And not because I would not have the time or the energy, but simply because I would not have the same level of emotional attachment to the subject matter (either the people or the occasions in the photos) and I believe that this would ultimately be reflected in the overall outcome. So hopefully these notes will help others to take on the same journey with their own families.

Vintage Photo Scanning – A Journey of Discovery

I recently undertook a project to scan and digitally convert a collection of vintage photographs belonging to my parents and wanted to share some of my findings, both from a technical and an emotional perspective. So if, like me, you discover a treasure trove of old photographs buried in a drawer somewhere in your parents house, don’t put them back, but do keep reading!

Parental Archives

Like many of my generation and the generations before me, I grew up in an almost exclusively non-digital era with an unwilling reliance on a minimal selection of analog TV and radio channels, cassette tapes and film cameras.

And while the invention of the Internet, coupled with services like YouTube, iTunes and Spotify has meant that many of the TV, radio and musical memories of my youth can be resurrected in the blink of an eye, alas the same does not hold not true for photographic memories. These are way harder to resurrect (impossible in some cases) as they cannot be reproduced or digitally remastered without the original content itself, which in most cases is in the possession of a single entity – your parents!

And this also means that you will require that your parents have done two things:

  1. Taken the time to capture photographs of your childhood in the first place;
  2. Ensure that these (and others of their own) were preserved intact over the intervening years.

And indeed the exact same applies to your parents and to the memories of the life they had before your arrival.


In terms of the equipment used to conduct this year-long exercise, here is what I needed:

  • Digital Photo Scanner: You don’t need to pay a lot of money for this (mine was a HP Deskjet F4580 that I bought for just €50), it just needs to support both Greyscale and Colour scanning (which most do) and at a decent resolution (300dpi).
  • Computer: Again, a relatively inexpensive laptop/desktop will be fine, although the scanning software can prefer a little extra RAM at times (when you’re scanning a lot of photos in a single session). Mine (actually, my wife’s) was a Dell Lattitude running Microsoft Windows.
  • Scanning Software: This may depend on your scanning device. I used to software that came with my scanner.
  • Graphics Software: As you are highly likely to want to crop some of the scanned images afterwards, you may need some additional graphics software for this. My personal open source favourite is GIMP, but there are lots to choose from and your scanning software may even do this for you anyway.
  • Post-its: These could prove really handy for cataloging and sorting the photographs so they can be reinserted into their original albums afterwards.
  • Exiftool: This a Unix command-line utility for injecting meta-data into digital image files, such as GPS location, date & time and names of those in the photograph.

Copious amounts of patience, coffee and beer are also strongly recommended.

Planning & Sorting

Strangely, one of the first challenges you’ll face is exactly how to remove the photos from their albums without damaging them and in such a way that you’ll be able to reinsert them in roughly the same order afterwards.

And don’t forget that, while you may feel that you project is complete once you’ve scanned the photos and have them on your laptop, your parents may want them restored into their original setting and you need to respect that.

So in my view, here is the best way to approach this:

  1. Devise an album/page numbering scheme and attach some post-its (or equivalent) to the pages in the various albums.
  2. Remove all of the Black & White photos first, because it’ll be more efficient to scan these together using the same scanner resolution/quality settings.
  3. As you remove each photo, write the album and page number on the rear, preferably using a pencil (which can easily be removed afterwards if required).
  4. Once removed, arrange the photographs into bundles of roughly the same size. This will also make for more efficient scanning (and cropping) of images later on.


Some of the photos may also be too faded, blurred, cropped or too small to be worth scanning so you may wish to omit those from the process early on. Similarly, keeping multiple (but very similar) photos of the same occasion (with the same people in them) can sometimes dilute the power of just one photo of that occasion.

This is just something you’ll need to make a personal judgement call on but you could use the following logic:

  1. Is there another, similar photo of the same occasion with the same people in it?
  2. Although it’s blurred, or of poor quality, is this the only photo with a particular person or group in it?
  3. Is there a favourite piece of music that this photo could go with, if you were to include it in a musical slide show or movie?

In my case, the percentage success rate here was actually only around 50% (i.e. I ended up skipping roughly half the entire collection) but given the nature of photographic technology at the time, this is not entirely surprising.

Testing, Trial and Error

The first thing you need to do once you think you are ready to start scanning is to stop and do some testing (with just a couple of photos) to be sure you are going to be happy with the results. Here, you are looking to settle on your optimum scanning technique and preferred resolution, file format, compression ratio, colour balance etc.

In terms of the file format, this is important too because not all formats are supported by the popular exiftool utility and so if you plan to inject metadata into the scanned images later on, you need to test this now so you do not use a format you will later regret. For example, I had scanned several hundred photos in PNG format before I realised that I could not inject metadata into them using the exiftool utility. I found that the JPEG format worked best for me.

So trust me, testing beforehand will save you a huge amount of time (and stress) later on, and you will thank me for warning you now.

Scanning & Cropping

In terms of the scanning effort itself, I found that scanning multiple (similarly sized) images at the same time was way more efficient. I also found it more efficient to crop the images from within the scanning software (that came with my scanner) before saving them to disk as separate images.

You might be forgiven for thinking this is the longest phase of the journey, but for me it wasn’t – the dating of the photos, naming of the image files and insertion of meta-data took a lot longer.

Naming Convention

In terms of how you name the image files produced by the scanning exercise, this is really a matter of personal preference. You could just stick with the arbitrary names assigned by the scanning software, but based on my experience you are far better off to invest a little extra time in devising a naming scheme for the files so that you can search for (and/or rearrange) them more easily later on.

What worked for me here was to construct the name of each file using 4 basic pieces of data, separated by a tilde character:



  • <Date> follows the standard YYYY-MM-DD date format. This means that the files will naturally sort themselves chronologically on most standard file browsing applications.
  • <Title> is some sort of snappy, 4-5 word title for the photo or event, possibly prefixed by a number if there are multiple photos taken on the same day at the same event.
  • <People> is a comma-separated list of the names of the people in the photo (as they would be commonly known to your family).
  • <Location> is a succinct description of where the photograph was originally taken (e.g. something that would match a search in Google Maps).

The use of a tilde character as the field separator (as opposed to a comma or hyphen, for example) is also optional, of course, but works well for me in many situations as it is rarely used within any of the other field/data types, thus allowing you to have commas and hyphens in those other fields without confusion.


Personally, I would not advise storing several hundred photos in a single directory as I think it would make them harder to manage, find and sort. I therefore decided to store batches of related files in a series of hierarchical subdirectories, some of which themselves included dates in their name. This is again a personal preference thing but it may work in your favour if you are planning to share a copy of the finished photo collection (on a USB stick or CD or via Dropbox) with friends and family.

Dating & Facial Recognition

This was by far the most enjoyable part of the journey. Not only did I learn so much about my wider family (and about myself) but the time I shared with my parents while undertaking this phase was hugely rewarding, both for them and for me. More mature readers will already know this, of course.

The facial recognition itself is relatively straightforward, in that your parents will either recognise the people or not, and it really doesn’t have to me any more complicated than that.

However, putting date on an old photograph can be a lot more difficult, especially when the folks are that little bit older. However, there are some tricks you can use to help with the accuracy here too, which essentially boil down to asking one or more of the following questions:

  1. We you married when this photo was taken?
  2. Was it before or after an important event in your life (e.g. Holy Communion, Confirmation, 21st Birthday, Wedding)?
  3. Was I (or any of my siblings) born when it was taken?
  4. Were your parents still alive when it was taken?
  5. Where did you/we live when that was taken?

By trying to evaluate the date of the photo in the context of seemingly unrelated milestones in their lives, you may find yourselves able to hone in on the real date with a reasonable sense of accuracy.

Are We There Yet?

At this point, you should have all of the photos scanned, cropped and named according to when they were taken, what the event was, who was in the photo and where it was taken. And for many people that would be more than enough.

However, the engineer in me was of course not happy to leave it at that. So watch out for my next blog post on how to inject metadata into your scanned images and use that to aid the importing of the photos into popular photo management software.


Google Street View launched in Ireland

Google have finally launched their Google Maps Street View service in Ireland. For those of you unfamiliar with this, it is the ability to zoom/pan down to ground level on a Google Map. I have used it once or twice but only really for US-based cities. However, it’s a wholly different (and addictive) experience using it to look at my own town, county and country.

The only down-side is that the simply isn’t obvious enough how to jump from a map view to the street view. To do this, you need to navigate to your location on the map view and then click and drag the small, yellow person icon (located above the zoom controls to the left of the map area) to the location on the map that you want to view the street view of.


Digital Camera Websites

While researching my recent purchase of a Canon Powershot SX200 IS, I considered each of the following websites (listed alphabetically):

There was actually €64 of a difference between cheapest (Simply Electronics) and the dearest (Expansys Ireland), for the camera only. However, Pixmania offered the best value for the package I wanted (i.e. spare battery, high-speed 8GB SDHC card and case) so I went with them in the end.

It was my first time shopping with Pixmania and I have say they provide a pretty good service. They provide an excellent tracking service (linked to DHL) and my package arrived safe and sound, and on time. The inclusion of a free Pixmania camera strap was a nice touch and my daughter was suitably impressed (as are her dolls who are now sporting said attire).

Canon Powershot SX200 IS

After seven years of faithful service, my trusty Canon IXUS V digital camera has finally been decommissioned. I originally won it on a radio phone-in competition back in 2002 and even though there’s actually nothing wrong with it functionally, I just found myself wanting more zoom on a number of occasions recently and so finally got around to upgrading. For it’s time, the IXUS V was a truly terrific camera – ultra compact, seriously rugged, 2 Megapixels, 2X optical zoom, video capture and superb picture quality.

On foot of the desire for more (optical) zoom, and with a preference to stick with Canon, I set about finding a replacement. Since High Definition movies and television are also the flavour of the month, I decided to go for something with HD movie capture too. Enter the Canon Powershot SX200 IS, with 12 Megapixels, 12X optical zoom, a 28mm wide angle lens, full 1080p HD video capture and a massive 3″ LCD screen, there isn’t much more I could have asked for.

If I were to have anything slightly negative to say about this camera it would be just that the pop-up flash takes a little getting used to. It would be great if it only emerged when actually needed. I also miss having a manual viewfinder. On the old model, I used to switch off the LCD display when running low on battery and use the manual viewfinder instead, yielding another 30 minutes of battery life instead. That said, I won’t be changing back any time soon and am looking forward to another 7 years of happy snapping.

Flickr Account Reviews

I recently created an account on the Flickr photography website for a friend and uploaded a couple of their pictures (3 to be precise) to get them started. I tagged each picture appropriately but found that they were not coming through on the RSS feed for that tag (something which I use Flickr for quite extensively).

After some searching, I found out (via a Flickr Forum Article) that:

  1. All new Flickr accounts must be reviewed before being accessible via the Flickr RSS feeds
  2. In order for a new account to be reviewed, you must have uploaded at least 5 public photos.

Since I had only uploaded 3 photos initially, this looks like the chief suspect for the behaviour that I’m seeing. I’ve uploaded some more now so will post back if/when the issue is resolved.

Beautiful Ireland by Joe Cashin

Two of my favourite photographs from the last year or so were both taken by Joe Cashin, an extremely popular contributor on Flickr and also an old friend of the family. Interestingly, both shots were taken in Co. Kerry and clearly demonstrate the truth in the statement that is omnipresent in Irish minds around this time of the year:

If only we had the weather

An Old Killarney Home (Muckross National Park, Kerry)

An old Killarney home

Evening on the Lakes (Killarney Lakes)

Evening on the lakes

Flickr Tag Galaxy

If you are fan of the Flickr photo sharing website, then you will enjoy Tag Galaxy. When you visit the site, just enter a tag (i.e. keyword, town, city, item) and it will show draw you an interactive galaxy representing related photos from the Flickr website. Here’s the galaxy for my home town of Tramore, Ireland:

Tag Galaxy - Tramore

You can then click on any one of the stars/planets/moons shown and it will draw a globe using the pictures from the associated tag. Here’s the globe for my home town:

Tag Galaxy - Tramore Globe

Source: Joe Cashin