Efficient FPGA architecture for oriented 1-D opening and pattern spectrum

This paper deals with a dedicated hardware architecture for 1-D morphological opening and pattern spectrum. These operators allow extraction and measurement of 1-D features in images that is a commonly used technique in image analysis and texture classification. The architecture is based on a recently proposed opening algorithm and makes it possible to obtain arbitrary-oriented opening and granulometry at the same time. Respecting a sequential data access, several instances with different orientation can run in parallel on a single input dataflow, increasing thus the performance (experimentally 414 Mpx/s per opening). It opens applicability of traditionally costly operators in embedded, industrial applications.