February 14, 2013 — Giulio Alessandrini, Mathematica Algorithm R&D

Mathematica 9 has just been released with many new or enhanced capabilities for image processing. You can perform morphological operations, color manipulation, segmentation analysis, feature detection, and more, most of which can be applied to the new Image3D object as well.

A byproduct of this whole ecosystem is that now it is easier than ever to use Mathematica to create and apply effects to your images.

Defining the new image

Two Mathematica super functions that can be used to apply transformations directly to an image are ImageApply, which is a pixel operator, and ImageFilter, which considers the pixel as well as a neighborhood of pixels around it and works as a local filter.

For example, you can remove the blue channel and perform a gamma correction only on the green channel by doing the following:

myfunction[{r_, g_, b_}] := {r, g^1.5, 0} ImageApply[myfunction, image]

Image with the blue channel removed and a gamma correction only on the green channel

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January 29, 2013 — Wolfram Blog Team

With Mathematica, you can bring new ideas into focus. No one knows that better than Fritz Lebowsky. He’s a senior principal engineer who does image-quality-related algorithm development for STMicroelectronics, a global manufacturer of electronics and semiconductors with advanced image processing technologies.

Thanks to Mathematica‘s advanced programming language and computational power, Lebowsky is seeing major advancements in his image processing development work, with his latest color imaging project set to double performance while reducing cost by half.

About the development, he says, “For the very first time in my research career I could combine several simple non-linear functions/dimensions to overcome some fundamental weaknesses in today’s linear mathematics applied to image processing.”

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January 4, 2012 — Shadi Ashnai, Manager, Image Processing

In a recent series of Image Processing with Mathematica workshops held at universities across the United States, we presented Mathematica‘s new image processing functionality and applied it on the spot to attendees’ real-world problems. It was amazing to me to see how rapidly and flexibly Mathematica could be applied to solve complex image processing problems. For example, it might seem like writing a program to automatically count cells in an image would be a master’s research project, but amazingly you can do it with a few lines of Mathematica code.

Below I am using morphological operations and measurement tools to segment and analyze red blood cells in a microscopy image.

Using morphological operations and measurement tools to segment and analyze red blood cells in a microscopy image

Cell segmentation and hole filling can be done with an intensity thresholding using Binarize and FillingTransform:

b = FillingTransform[ColorNegate[Binarize[rbc]]]

Using Binarize and FillingTransform to show cell segmentation and hole filling

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November 21, 2011 — Matthias Odisio, Mathematica Algorithm R&D

We just attended the International Conference on Image Processing (ICIP) in Brussels and the 14th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in Toronto. Both events proved to be great occasions to demonstrate how Mathematica can aid research in image processing, from investigation and prototyping to deployment. Last but not least, we seized the opportunity to listen to the experts in the field to extend the functionality of Mathematica in the right direction.

Last year, Ruogu Fang, Kevin D. Tang, Noah Snavely, and Tsuhan Chen received the best paper award at ICIP for their study of kinship detection from pairs of images. I decided to build a detector by following their proposed framework with Mathematica.

A lot has been said and studied about our human ability to recognize faces; computer programs can be quite good at it, too. Similarly, when looking at faces, we may display a canny ability to detect an ancestry relationship, or kinship.

John F. Kennedy and John F. Kennedy Jr.

In these pictures, is the person on the left the father of the person on the right? Yes, and we can figure it out with Mathematica.

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September 9, 2011 — Jon McLoone, International Business & Strategic Development

As a change from my usual recreational content, today I thought I would describe a real Mathematica application that I wrote. The project came from my most important Mathematica user—not because she spends a lot of money with Wolfram Research, but because I am married to her!

Her company, Particle Therapeutics, works on needle-free injection devices that fire powdered drug particles into the skin on a supersonic gas shock wave. She was trying to analyze the penetration characteristics on a test medium by photographing thin slices of a target under a microscope and measuring the locations of the particles.

Photograph of thin slices of a target under a microscope and measuring the locations of the particles

The problem was that her expensive image processing software was doing a poor job of identifying overlapping particles and gave her no manual override for its mistakes.

Faced with the alternative of holding rulers up to her screen and recording each value by hand, I promised that I could do better in Mathematica, with the added advantage that now her image processing tool would be integrated into her analysis code to go from image file to report document in a single workflow.

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June 23, 2011 — Yu-Sung Chang, Technical Communication & Strategy

Creating an interactive app could be a complex and painstaking task. Not with Mathematica. Here I will present how I created a photo booth program in three easy steps—mostly during my lunch breaks.

Step One: Architecture

Four stages

The application will have four main stages. Stage one: We show live webcam images with different image effects applied (possibly multiple pages of them) as a preview, and let the user choose one. Stage two: The chosen image takes up the window, waiting for the user to click a button. Stage three: Count down. Stage four: Capture an image, apply the effect, and add it in a film strip. Repeat.

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February 1, 2011 — Daniel Lichtblau, Scientific Information Group

When last seen in the whereabouts of the Marlborough Maze, I was slinking off stage left, having been upstaged by Jon McCloone and his mix of image processing and graph theory alchemy. In a comment on my post, Jaebum Jung showed similar methods.

Me, I only wanted to compute a bunch of distances from the entrance, then walk the maze. But I was not at that time able to show which was the shortest path, or even to prune off the dead ends. I’m over that lapse now. In this post I will provide brief Mathematica code to take the grid of maze pathway distances that I computed, and get the hopeless paths to melt away. Technically this is referred to as a retraction—not in the sense of an apology, but, rather, topology.

Marlborough Maze

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December 21, 2010 — Jon McLoone, International Business & Strategic Development

Regular readers of the Wolfram Blog will have seen that the item that I wrote on solving mazes using morphological image processing was thoroughly beaten by the much smarter and better read, Daniel Lichtblau from our Scientific Information Group in his post “Navigating the Blenheim Maze”.

Always up for a challenge (and feeling a little guilty about the rather hacky and lazy way I tried to deal with loops and multiple paths the first time), I am back for another go.

My first approach with any new problem is to think about the nearest available Mathematica command. In the new Mathematica 8 features is a graph theory command FindShortestPath. That certainly sounds promising.

Mixing image processing and graph theory may sound complicated, but one of the central strengths of Mathematica‘s integrated all-in-one design is that different functionality works together, and in this case it proves to be quite easy.

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December 7, 2010 — Daniel Lichtblau, Scientific Information Group

I read Jon McLoone’s recent “aMazeing Image Processing in Mathematica” post with some interest.

It showed how to import an image of a maze, and then use image processing functions in Mathematica (some new to Version 8) to draw paths through the maze. What fun! I then observed, to my dismay, that there was no way to determine a “good” path. Frankly, I was disappointed.

I decided that there must be ways to do this in Mathematica. One approach would involve forming a graph. We would have vertices at points where the maze path forks, and we would make weighted edges from approximated distances between these vertices. New functionality in Mathematica supports these graph methods. Unfortunately I am not yet familiar with it.

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November 10, 2010 — Jon McLoone, International Business & Strategic Development

Ever since I wrote the “Doing Spy Stuff with Mathematica” blog post, I have had a feeling that I am being watched. Time to build some office security using Mathematica Home Edition!

First, I am going to make use of an imminent new Mathematica command CurrentImage, which will import a real-time image from a video device. Let’s get some test images using the webcam on my laptop.

Imported real-time test image

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