The document presents a novel technique for edge contour extraction, focusing on detecting edge regions with high gradient magnitude and a common quantized gradient direction. It highlights the advantages of processing only significant portions of an image, potentially reducing computation effort while effectively managing noise and outliers. Experimental validations via inter- and intra-technique evaluations demonstrate the technique's efficiency in generating accurate edge contour maps.

1. An edge contour
extraction technique
Ivan Cabezas and Maria Trujillo
Universidad del Valle, Cali - Colombia
Panos Liatsis
City University, London - UK

2. Outline
Introduction
The Proposed Technique
Edge region detection
Edge contour extraction
Effects of Outliers
Experimental Validation
Inter-technique evaluation
Intra-technique evaluation
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3. Introduction
An edge can be described
as a local luminance
change
Edge detectors produce
disjoint edge segments
stored in binary maps
Edge contours are
relatively invariant to the
changes of illumination,
and sensor characteristics,
among others
CLEI 2008 - An edge contour extraction technique Slide 3 / 16

4. Introduction
A contour can be represented using an ordered chain of
symbols which links an initial edge point to a final edge
point
For instance: { [70,45],2,3,2,3,3,2,3,3,3,2, . . .
3,4,3,4,3,4,3,4,3,4,[17,32] }
[17,32]
[70,45]
3 2 1
4 C 0
5 6 7
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5. Edge Region
An edge region is a set of adjacent points with
a gradient magnitude higher than a threshold
and a common quantised gradient direction
Magnitude 0 0 0 40 40 0 0 0 Magnitude 0 0 0 10 20 10 0 0 0
Gradient Gradient
Direction Direction
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6. Edge Region Detection
A quantisation is used in order to establish
common gradient directions
135º 90º 45º
180º 0º
225º 270º 315º
Quantisation
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7. Edge Contour Extraction
There is a region when at least
two contiguous points with high
gradient magnitude have the
same quantised gradient direction
An edgel is located by performing
non-maximal suppression
The continuity of the edge region
and the adjacency of located
edgels allow tracking edgels
CLEI 2008 - An edge contour extraction technique Slide 7 / 16

8. Innovative aspect
The proposed technique does not process the
entire image for extracting edge contours
Points processed by Points processed by Edge contours extracted
traditional edge the proposed technique by the proposed technique
extraction techniques
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9. Effects of Outliers
Original Signal Gradient Directions
Signal plus Noise
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10. Edge Contour Extraction with Noise
An outlier point can have a high gradient
magnitude but it causes a gradient direction
peculiarity in its neighbourhood
The presence of outliers in an edge region
causes deterioration in edge maps computed
by the proposed technique
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11. Inter-Technique Evaluation
FPP = FP / (TP+FN) TPR = TP / (TP+FN) FPR = FP / (FP+TN)
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12. Inter-Technique Evaluation
“Egg” Ground Truth
The Sobel The Canny The proposed technique
CLEI 2008 - An edge contour extraction technique Slide 12 / 16

13. Intra-Technique Evaluation
FPP = FP / (TP+FN)
CLEI 2008 - An edge contour extraction technique Slide 13 / 16

14. Intra-Technique Evaluation
Edge Contour Maps
Search densities and processed points
247 62 31 16
CLEI 2008 - An edge contour extraction technique Slide 14 / 16

15. Conclusions
Edge contours are thin chains of edgels with
maximum gradient magnitude and a common
gradient direction
The computation effort is reduced using a set
of columns and/or rows
It is possible to obtain a edge contours map
by processing 50% or less of an image,
depending on the image content
CLEI 2008 - An edge contour extraction technique Slide 15 / 16

16. Questions
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