  The performance of an edge detector can be improved when assisted with an
effective edge map quality measure. Several evaluation methods have been
proposed resulting in different performance score for the same candidate edge
map. However, an effective measure is the one that can be automated and which
correlates with human judgement perceived quality of the edge map.
Distance-based edge map measures are widely used for assessment of edge map
quality. These methods consider distance and statistical properties of edge
pixels to estimate a performance score. The existing methods can be automated;
however, they lack perceptual features. This paper presents edge map quality
measure based on Just-Noticeable-Difference (JND) feature of human visual
system, to compensate the shortcomings of distance-based edge measures. For
this purpose, we have designed constant stimulus experiment to measure the JND
value for two spatial alternative. Experimental results show that JND based
distance calculation outperforms existing distance-based measures according to
subjective evaluation.
