Kylberg Sintorn Rotation Dataset

During my Ph.D. studies at Uppsala University, I acquired and published three texture datasets, I have had requests on hosting these datasets on additional locations other than the university server (address Here is an overview: link

Figure 1. Examples of the 25 texture classes.

Short description

  • 25 texture classes, see Figure 1.
  • 100 samples per texture class.
  • Samples are 122×122 pixels in size.
  • The textures has been rotated using hardware and rotated by interpolation using, nearest neighbour, linear, 3rd order cubic, B-spline, and Lanczos 3 kernels.
  • All texture samples are normalized with a mean value of 127 and a standard deviation of 40.


Kylberg Sintorn Rotation dataset

The compressed files are roughly 240 MB in size each.

  • Hardware rotated texture samples. [.zip, .7z]
  • Rotated texture samples using nearest neighbour. [.zip, .7z]
  • Rotated texture samples using linear interpolation. [.zip, .7z]
  • Rotated texture samples using 3rd order cubic interpolation. [.zip, .7z]
  • Rotated texture samples using B-spline interpolation. [.zip, .7z]
  • Rotated texture samples using Lanczos 3 interpolation. [.zip, .7z]

Original Images

  • RAW-originals (~6 GB)
  • PNG-originals (~6 GB)

How to reference

If you use the texture dataset in your research or in any other way, please refer to it as:

Kylberg, G., Sintorn, I. On the influence of interpolation method on rotation invariance in texture recognition. J Image Video Proc.2016, 17 (2016).