Built with materials including LEGO^©, 5 acrylic mirrors, a base and specimen holder inset cut from Formex (Fig. 1a-d). Materials used were chosen to ensure easy and cost effective replication. As a prototype MALICE is built to be configurable with easy adjustment of mirror tilt to accomdate different vial sizes. Mirror tilt is achieved using a friction joint (Fig. 1e). Once an optimal mirror angle is chosen, the setup can be built out of any suitable material. For testing the MALICE base plate was attached to a Kaizer RS10 copy stand with re-usable adhesive putty (Blu Tack) during imaging. Images were taken using a Canon 5DSR and Canon 24-70mm lens, controlled with EOS Utilities v.3.

Imaging: A vial is removed from the jar, placed in the centre of the MALICE setup, with a unique identifier (UID) label, encoded as a barcode, placed horizontally next to it. A single image is taken from above,capturing five views of the vial in the mirror images. The vial is then opened andthe barcode label is inserted. The vial is then re-sealed and placed back in the original jar.

Processing:

1. Images were renamed with Gouda, using the command: "decode_barcodes.exe -a rename --avoid-collisions libdmtx "path to files"".
2. The five vial reflections were cropped out of the image using Adobe Photoshop (CC 2019).
3. Cropped images were manually deskewed, rotated and reflected using Photoshop creating a composite image.

Images were taken using a Nikon D5300 camera. Specimen vials were placed on a Stackshot rotary table with controller (https://www.cognisys-inc.com/store/rotary-table.html) (Fig. 2) Both the camera and rotary table were controlled using Helicon Remote v.3.9.1.

Imaging: A vial is removed from the jar, placed in the centre of the rotating stage, with a UID label, encoded as a barcode placed vertically on a stationary stage within the imaging frame. Images are taken at six different angles corresponding to 0, 72, 144, 216, 288 and 360 degrees. The vial is then opened, the UID label inserted, the vial re-sealed and placed back in the original jar. The arbitrary degree between the images reflects a mistaken configuration of the stackshot turntable resulting in the duplication of the initial view with that of 360 degrees, which was subsequently deleted. Future imaging should utilise 0, 60, 120, 180, 240, 300 degrees to maximise label views while removing duplication.

Processing: Image processing followed these steps:

1. Images were renamed with Gouda, using the command: "decode_barcodes.exe -a rename --avoid-collisions libdmtx "path to files"".
2. Images were cropped, minimizing extra space, with XNConvert v1.76, saving the output images as JPG at 90% quality.
3. Stitch 5 images together using mageMagick 7.0.7 ( https://github.com/ImageMagick ) with a recursive script based on the image name (e.g. “magick 013670425-4.jpg 013670425-3.jpg 013670425-2.jpg 013670425-1.jpg 013670425.jpg +append 013670425_combined.jpg”)

Camera, turntable, controller and lighting were built into a formex casing. The setup presented uses a Canon 5DsR camera with a 100mm Canon macro lens for capturing video and still images. The turntable is custom-built using 2mm aluminum, and polystyrene sheets. Movement of the turntable is provided by a 5v stepper motor (28BYJ-48 5V) controlled by a drive chip (ULN2003) and an Arduino UNO. Lighting was provided by 3 COB 48-SMD LED panels for front lighting and a Neewer 40004082 light panel for backlighting (Fig. 3a-e). To ensure camera, turntable and lightshield (Fig. 3f) alignment as well as XYZ adjustment the camera, the turntable and light shield were mounted on a Small Rig rail system.

Imaging: A vial is placed in the centre of the turntable and filmed over a 720 degree rotation. Rotating the vial multiple times ensures that all possible angles are covered. The setup is calibrated by taking a single frame of a scale at the centre of the turntable and using image software to estimate the width (in pixels) of a single millimeter. The number of frames \(n_f\) required can then be calculated as such:

\(n_f = {2\pi dlxw_1 \over 2lx-dsw_1}\)

Where \(d\) is the vial diameter (in mm), \(l\) is the focal length (in mm), \(x\) is the size of the frame (in pixels) across the x axis of the vial (i.e. width if landscape, height if portrait), \(s\) is the size of the sensor (in mm) across that same x dimension, and \(w_1\) is the width of 1mm in pixels (obtained during the calibration step).

The duration of a single rotation can be calculated by dividing this figure by the stream's framerate: \(t = {n_f \over r}\)

This figure is largely a helpful estimate and high levels of accuracy are not necessary; it is preferable to err on the side of longer rotations to ensure that detail is not missed.

In the example dataset, videos were captured at approximately 60 frames per second, at a focal length of 100mm and a resolution of 1280x720 pixels (in portrait orientation). The size of the sensor on the Canon 5DSR is 36x24mm. The width of 1mm on the calibration frame was approximately 21 pixels.

For a 10mm vial: \(n_f = {2\pi \times 10 \times 100 \times 720 \times 21 \over 2 \times 100 \times 720 - 10 \times 24 \times 21 } = 684\) and \(t = {684 \over 60} = 11.4\)

For a 20mm vial: \(n_f = {2\pi \times 20 \times 100 \times 720 \times 21 \over 2 \times 100 \times 720 - 20 \times 24 \times 21 } = 1419\) and \(t = { 1419 \over 60} = 23.7\)

Processing: ReVILE is capable of producing 3 separate image outputs outlined in the results section. The primary output is the composite rolled out image. The workflow of the rollout photography output is outlined below and the potential for the other two outputs - a composite image of the vial at different angles (equivalent to the VILE output) and an interactive digital-only output that allows for user rotation of the imaged vial - are examined in the discussion.

Custom software was developed to control the camera and turntable as well as process the camera’s outputs to produce the rolled out image of the object. This software is available at https://github.com/NaturalHistoryMuseum/revile.

Once the object has been securely positioned on the turntable in front of the camera, the software follows the following steps to produce the rolled out image of the object:

1. Initialise the video capture process - this is done first as it takes a couple of seconds to begin capturing, but step 2 should generally begin first;
2. Start rotating the turntable for the specified number of seconds;
3. Iterate through the stream or video frames, extracting the middle column or row (depending on camera orientation) of pixels from each frame;
4. Concatenate the extracted lines of pixels from each frame together to build the image;
5. Undertake any postprocessing steps, e.g. rotating the output;
6. Crop the image so that it shows only one complete rotation, using feature matching to locate similar columns of pixels; and
7. Write two JPEG images to disk: the complete, "raw" output, and the cropped version.

Using the hardware setup pictured in Fig. 3, the middle row of pixels is extracted from each frame as the camera is positioned on its side. The concatenated image is rotated through 270 degrees to turn it the right way up before being written to disk.

The speed of the turntable’s rotation is determined by the diameter of the object being processed. Wider objects, such as a jar, require a slower rotation while thinner objects, such as a vial, can be rotated faster. The software provides an estimate function through its command line interface (CLI) which can be used to guess the rotation duration for the object given its diameter in mm, number of pixels per mm as seen by the camera (by default, 21) and the source frame rate (either the stream frame rate or the video frame rate).