What is ImageJ and how is relevant to my research?

29 10 2013


ImageJ (inherently Fiji)  is an open source image processing program developed by the National Institute of Health (Maryland, USA) in 1997 has been described as ‘the standard in scientific image analysis (XXIV Focus on Bioimage Informatics, 2012).  As with most public domain projects, ImageJ was developed with an open architecture that is conducive to plugins that add expand functionality to the software. Essentially ImageJ was developed to work as an editor and Java compiler to process and analyze large data sets of images in the field of health science.

ImageJ’s current functionalities as described on http://rsb.info.nih.gov are listed as  follows:

–       It can display, edit, analyze, process, save and print 8-bit, 16-bit and 32-bit images. It can read many image formats including TIFF, GIF, JPEG, BMP, DICOM, FITS and “raw”.

–       It supports “stacks”, a series of images that share a single window. It is multithreaded, so time-consuming operations such as image file reading can be performed in parallel with other operations.

–       It can calculate area and pixel value statistics of user-defined selections. It can measure distances and angles.

–       It can create density histograms and line profile plots.

–       It supports standard image processing functions such as contrast manipulation, sharpening, smoothing, edge detection and median filtering.

–       It does geometric transformations such as scaling, rotation and flips. Image can be zoomed up to 32:1 and down to 1:32.

–       All analysis and processing functions are available at any magnification factor.

–       Spatial calibration is available to provide real world dimensional measurements in units such as millimeters.

–       Density or gray scale calibration is also available.


Although originally developed for biomedical researchers using microscopes, is clear the image processing tools inherent in the program could prove useful in any field of research that requires the analysis and visual representation of large image data sets.

As part of the Software Studies Initiative of the California Institute for Telecommunication and Information Technology (Calit) a project has emerged that has expanded the applications of ImageJ in the study of Digital Humanities.  Cultural Analytics, developed by Lev Manovich in 2005, is developing research  methodologies around data-driven cultural analysis. The mandate of Cultural Analytics is to “create more comprehensive and inclusive understanding of human cultural evolution and dynamics using all available digitized and born-digital cultural artifacts in any media from all of human history.” (http://lab.softwarestudies.com/2008/09/cultural-analytics.html).

Comparison of Obama TV ads

‘Image Map’ Comparison of Obama TV ads.
x-axis = mean grayscale value for all pixels in single frame
y-axis = mean standard deviation for pixel grayscale values in single frame

Ima‘Image Map’ Comparison of McCain TV adsge

‘Image Map’ Comparison of McCain TV ads.
x-axis = mean grayscale value for all pixels in single frame
y-axis = mean standard deviation for pixel grayscale values in single frame

Through the visualization of large cultural data sets the project maps patterns in existing digital artifacts. Projects include the visualization of the 2008 US Presidential online video ads that mapped out each frame of twelve campaign ads from Barak Obama and John McCain and organized them visually according to greyscale. Other notable projects include the visualization of Vincent Van Gogh’s work.

This project is relevant to my own research in that I am seeking a method in which to visualize the Philippine diaspora community. Inherent in this research is the analysis of large sets of images. The first data set I came across in my study of the ‘Philippine visual identity’ was the fronds at the Archivo General de Indias in Seville which housed several thousand drawings of colonial Philippines date back to as early as 1555.  The process I initially took to visualize these archives involved the collage of several choice images with my own photography and painting to create a pastiche that used colonial maps to explore the complexities of Philippine history from a postcolonial lens.

I am eager to use some of the methods of analysis in Manovich’s Cultural Analytics project towards the visualization of the Seville archives and possibly more image sets that I come across in my research.

New directions

28 10 2013

Writing a doctoral thesis can be a long and lonely test of endurance and confidence. I’ve spent the last three years starting and stopping this particular dance. Things I’ve learned along the way are that:

1. The biggest of feats can only be accomplished by the successive and persistent completion of small goals. The scale of a PhD project is by no means a lifetime’s amount of work, but before you’ve crossed the threshold of a complete and solid draft, the 200,000 words or more (plus art in my case) can seem daunting. My struggle has been to stay motivated but I’ve found breaking down the project into bite-sized pieces has helped me to deal.

2. Plans are meant to be changed. As I reach another crossroad in my research I’m finding that I have to pair the project down again. I started things with big dreams to create a project that connected Philippine digital artists, visually represented the diaspora community in real-time, and spoke to a greater trend of open sharing facilitated by the internet and ICTs. Rather lofty aspirations which are all entirely valid and attainable however maybe not realistic for one mere PhD Project. Maybe so if I wanted to complete my PhD in 20 years but as it stands I know of know of no post-graduate program or funding body that will support such work from a PhD candidate 😉 Garnering support is a process and for now it is essential that I pair the work down to a scale that fits my current time and financial restrictions. This in fact makes the project more focussed and valid and most importantly more able to see the light of day.

3. Stay focussed. Don’t take on too much. In the course of doing this research, as it is with most eager and able post-graduate researchers exciting opportunities perpetually dangle within your field of view. I have designed and taught a digital humanities course about networked communities, I have presented my papers at exciting conferences in the UK and Canada and have initiated several research projects one of which perpetuated dialogue between scholars in OCAD University and Goldsmiths. All of these are important to the larger picture of a healthy and vibrant academic career, but none of these are as important as getting the PhD done.

And so I am here. I have officially completed 2 years and am currently in my second year of ‘official interruption’. I started the  project in the 2010-11 academic year. Took leave 2011-12 for the birth of my beautiful daughter (the second of my little monsters). Returned for furiously fast year 2012-13 where I taught, wrote, initiated projects, bought a house, watched my eldest start school and my dad start dialysis treatments for his renal failure. And now, 2013-14, I am on leave again recovering from a badly broken collarbone that required the surgical implant of substantial piece of metal in my shoulder (I have a medical note for metal detectors and I can forecast the onset of a storm better than my iPhone). While I heal my broken wing, I will make art, write, make art, write and write some more.  My plan is to get this PhD done within two years.

One significant shift that has occurred is that I am consciously putting ‘the practice’ back into the ‘practice-based PhD’.  Somewhere along the way I got lost in the engagement of literature and conferences and writing and I am trying to tie this all into to my art practice. I of course have the work I have done with the data set of images in the colonial archives in Seville, Spain but I am currently looking into a project a came across several years ago spear-headed by Lev Manovich. Manovich’s Cultural Analytics project hacks a medical visualization program initially meant for (MRIs?)  called ImageJ to create visualizations that explore the large data sets of images being generated by social media, film, design, etc. The project is open source so welcomes public exploration into newer avenues. In fact, in a talk by Manovich at OCAD University in 2011, he was hoping to encourage public adoption of this project to possibly deepen and widen the scope of this method of cultural analysis.

I aim to use this method to visualize the presence of the Filipina online. A large part of the current Philippine diaspora has started from the initial casting of women as domestic labourers along foreign shores to work as care givers in the homes of young families and the elderly.  These women save a potion of their wages to send back ‘home’ to their children and families and they are leaving a digital trail in online communications as they work to stay in connected with the lives they left behind.

I hope to embark on this project as a continuation of my initial visual exploration of the archives in Seville. Both these initiatives help to define and visualize the Philippine diaspora.

Life is a rich and exciting journey. While I am healing my broken wing I am working on completing the little things, staying flexible and maintaining focus.