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How to Detect Image Manipulations Part V: The Subtraction Tool in ImageJ


By Dr. Thorsten S. Beck

2. April 2019

beck@headt.eu

As already outlined in Part IV of this series, the image editing program ImageJ, developed by Wayne Rasband under the auspices of the United States National Institute of Health, offers a wide range of image editing possibilities, as well as a wealth of tools and extensions that can be used for measuring and analyzing images.

THE PROBLEM

One of the obvious challenges when screening scientific images is to reliably identify elements that have been added subsequently. In the following experiment we are going to test the capacities and limitations of the subtraction operation in the Image Calculator – one of the tools available in ImageJ. We find this tool in the drop-down menu under ‘Process’ (see Fig. 1).

Fig. 1: Image Calculator in ImageJ

To test how effective the Image Calculator is, we think of a scenario in which an element has been copied into an image. The Image Calculator should be able to identify this very element. I generated the following three examples to use them for this test.

EXAMPLES FOR TESTING

In the first example (see Fig. 2 for the original image), one of the individual bees has been copied, moved and pasted into the image (see Fig. 3). Compared to the original image, it becomes clear how difficult it is to perceive this manipulation with the naked eye. Even the trained eye has difficulties to clearly identify such copied and re-used picture elements when there are many of the same kind.


Fig. 2: Original Image



Fig. 3: Image with bee added.

In example 2 we apply this basic operation to an electrophoresis image to simulate a scenario in scientific research. An image element from the original image is duplicated and reused several times (see Fig. 4). Here, too, we will test how effectively the Image Calculator can help to identify and highlight this manipulation.

Fig. 4: Electrophoresis Image (Original on the left, and altered version on the right.)

In the third and last example (see Fig. 5 for the original image), one of the elements is removed from the photo using the Clone Stamp in Photoshop (and overwritten with background texture). Another element is copied and used to replace the removed element (see Fig. 6). The resulting image will then also be analyzed with the help of the ImageJ subtraction tool in the Image Calculator.

Fig. 5. Original Image


Fig. 6: Manipulated Version: Image element deleted with Photoshop Clone Stamp and pliers (Pos. 4 on the right) copied and pasted.

WORKING STEPS AND ANALYSIS 

In order to analyze the test images, a reference image is required as a source for comparison for each of the examples. Here are some instructions of the steps that must be performed one after the other in the program: First, the source image and the manipulated version are dragged and dropped onto the ImageJ tool bar. Both images are now displayed automatically and the Image Calculator opens. To determine the difference between both versions, the operation 'Subtract' (the original version is subtracted from the manipulated version) is selected (see Fig. 7). The result image clearly reveals the difference that was so difficult to see with the naked eye (see Fig. 8).

Fig. 7: Image Calculator Menu


Fig. 8: Subtraction Result of Bee Example Image

We proceed similarly with the second example. Here, too, the operation produces a quite clear result. The subsequently added blots are clearly displayed, while all identical image information remains black (see Fig. 9).

Fig. 9: Subtraction Result of Electrophoresis Example Image

Somewhat less clear, but still clear enough, is the result of the third experiment. The Image Calculator shows both copied and moved image element as well as the cloned region and the image information that is actually covered by the image background (see Fig. 10).

Fig. 10: Subtraction Result of Tool Example Image

SUMMARY AND EVALUATION

The Image Calculator in ImageJ reliably determines the differences between non-manipulated source images and manipulated versions – upon visual inspection. Especially for images with elements that are somewhat difficult to clearly identify and analyze for the naked eye, this tool appears to be a good help.

The procedure presented here, however, is an idealized scenario. The tool will only produce such impressive results if the original version of the modified image is available and can be compared with the manipulated image. But that is rarely the case in real-world scenarios. Even if the journal instructions would require authors to submit the original data of their images along with the publication, a small change to the manipulated image is enough to significantly reduce the efficiency of the Image Calculator. As soon as the dimensions of the image are not identical, the program calculates a completely different result:

 

Fig. 11: Subtraction Result with Cropped Reference Image

In summary, the ImageJ subtraction tool has delivered surprisingly clear and comprehensible results, but facing the limitation that these were artificial conditions.

Given the precondition that original and reference image are both available (and not cropped or stretched) for analysis, the program delivers consistent and convincing results. It goes without saying that reality tends to be somewhat more complicated than hand-made test conditions.

More tools will be evaluated soon – please visit HEADT.EU for upcoming posts.


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