  In this paper we consider speedup potential of morphological image filtering
on ARM processors. Morphological operations are widely used in image analysis
and recognition and their speedup in some cases can significantly reduce
overall execution time of recognition. More specifically, we propose fast
implementation of erosion and dilation using ARM SIMD extension NEON. These
operations with the rectangular structuring element are separable. They were
implemented using the advantages of separability as sequential horizontal and
vertical passes. Each pass was implemented using van Herk/Gil-Werman algorithm
for large windows and low-constant linear complexity algorithm for small
windows. Final implementation was improved with SIMD and used a combination of
these methods. We also considered fast transpose implementation of 8x8 and
16x16 matrices using ARM NEON to get additional computational gain for
morphological operations. Experiments showed 3 times efficiency increase for
final implementation of erosion and dilation compared to van Herk/Gil-Werman
algorithm without SIMD, 5.7 times speedup for 8x8 matrix transpose and 12 times
speedup for 16x16 matrix transpose compared to transpose without SIMD.
