The document introduces a novel digital hardware architecture called OSLCR for accelerating form-based image preprocessing using morphological operations. OSLCR enables more efficient implementation compared to direct realization by reusing comparisons along discrete shift levels as the structuring element is displaced over the image. An implementation of OSLCR achieved a 44% reduction in chip area and approximately six times higher maximum clock frequency compared to direct realization for erosion/dilation using a 13x13 diamond-shaped structuring element on 8-bit graylevel images. The researchers are seeking business and investment opportunities to further develop and commercialize the OSLCR approach.

1. Accelerating Form Based Image Preprocessing with
Digital Hardware
Markus Holzer, Thomas Greiner
Pforzheim University
Center for Applied Research - MERSES
10th Heidelberg Innovation Forum, Studio Villa Bosch 12th April 2011

2. Outline
• Introduction to form based image processing with
Morphological Operations
• Novel principle (OSLCR) of efficient digital hardware
realization of Morphological Operations
• Architectural performance and hardware
complexity of OSLCR
• Requirements concerning the transfer business

3. Introduction to Form Based Image
Processing with Morphological Operations
What are Morphological Operations?
Non-linear
Image
neighborhood Discrete 2D
processing
operations

4. Introduction to Form Based Image
Processing with Morphological Operations
Application fields
• Image filtering / enhancement
• Noise reduction, object contour smoothing
• Object segmentation
• Content based image/video coding/compression
• Pre-processing for computer vision
• Object analysis and measurement
• Object summaries related to e.g. form attributes,
texture, orientation (e.g. for granulometry)
• Exploration object topology (e.g. for OCR)
Major advantages
• Can remove artifacts without smearing significant object edges
• Efficiently implementable (especially for binary images)

5. Description of Morphological Operations
• Compositions and repetitions of two
basic operations: erosion and dilation
– 2D gray level input image G
– 2D binary / gray level signal: flat / non-flat
structuring element (SE) defines the
decisive form signature
• The Input Image is probed with SE
– SE is shifted over the entire input
image pixel-wise in raster scan mode
– For each shift step:
• The minimum / maximum in the
scope of SE must be found
• The pixel of output image G flat structuring element
congruent to the actual reference pixel
reference point of SE is set to
this minimum / maximum value

6. Example
Erosion with flat SE: 8 bit gray level input image
G
13 ×13 diamond shaped SE

7. Example
Erosion with flat SE: 8 bit gray level input image
G
13 ×13 diamond shaped SE

8. Example
Erosion with flat SE: 8 bit gray level input image
G
13 ×13 diamond shaped SE

9. Example
Erosion with flat SE: 8 bit gray level input image
G
13 ×13 diamond shaped SE

10. Example
Erosion with flat SE: 8 bit gray level input image
G
13 ×13 diamond shaped SE

11. Example
Erosion with flat SE: 8 bit gray level input image
G
13 ×13 diamond shaped SE

12. Example
Erosion with flat SE: 8 bit gray level input image
G
• Observation: between subsequent line wise shift steps

13. Example
Erosion with flat SE: 8 bit gray level input image
G
→ pixel overlay → redundant comparisons
→ for large-area SE direct implementation is inefficient
– direct implementation of 13×13 diamond shaped SE
→ 84 comparisons per shift step

14. OSLCR Architecture Principle
OSLCR: Orthogonal Shift Level Comparison Reuse
•SE shape independent digital hardware design approach
•Principle: Comparisons along discrete shift levels (DSL)
are reused (orthogonal to the shift direction) while the SE
is displaced line-wise over the image

15. OSLCR Architecture Principle
OSLCR: Orthogonal Shift Level Comparison Reuse
•SE shape independent digital hardware design approach
•Principle: Comparisons along discrete shift levels (DSL)
are reused (orthogonal to the shift direction) while the SE
is displaced line-wise over the image

16. OSLCR Architecture Principle
OSLCR: Orthogonal Shift Level Comparison Reuse
•SE shape independent digital hardware design approach
•Principle: Comparisons along discrete shift levels (DSL)
are reused (orthogonal to the shift direction) while the SE
is displaced line-wise over the image

17. OSLCR Architecture Principle
OSLCR: Orthogonal Shift Level Comparison Reuse
•SE shape independent digital hardware design approach
•Principle: Comparisons along discrete shift levels (DSL)
are reused (orthogonal to the shift direction) while the SE
is displaced line-wise over the image

18. OSLCR Architecture Principle
OSLCR: Orthogonal Shift Level Comparison Reuse
•SE shape independent digital hardware design approach
•Principle: Comparisons along discrete shift levels (DSL)
are reused (orthogonal to the shift direction) while the SE
is displaced line-wise over the image
•Less comparisons per shift step -> enhance processing
speed and hardware complexity

19. Architectural performance and hardware
complexity analysis
Implementation of
erosion / dilation by Several SE shapes were realized in digital hardware
OSLCR concept and (VHDL on register transfer level)
direct realization
Architecture Nand2 Gate Equ. relative max.
For e.g. diamond shaped frequency
13 × 13 SE, 8 bit gray level
input image Direct realization 14,976 1.0
This work (OSLCR) 6,576 6.17
Compared to direct realization 44% of Approximately six times higher maximum
chip area clock frequency

20. Requirements concerning the transfer
business
• We are looking for: Business Partners,
Investors, Buyers of Licenses.
• We want to achieve: Research and
Development Cooperation, Investment,
Commercialization.
Please contact us for further information:
markus.holzer@hs-pforzheim.de,
thomas.greiner@hs-pforzheim.de.

21. The End
Thank you for your attention…
Please contact us for further information:
markus.holzer@hs-pforzheim.de,
thomas.greiner@hs-pforzheim.de.