Perceptually-based Comparison of Image Similarity Metrics

The image comparison operation ??sessing how well one image matches another ??rms a critical component of many image analysis systems and models of human visual processing. Two norms used commonly for this purpose are L1 and L2, which are specific instances of the Minkowski metric. However, there is often not a principled reason for selecting one norm over the other. One way to address this problem is by examining whether one metric better captures the perceptual notion of image similarity than the other. With this goal, we examined perceptual preferences for images retrieved on the basis of the L1 versus the L2 norm. These images were either small fragments without recognizable content, or larger patterns with recognizable content created via vector quantization. In both conditions the subjects showed a consistent preference for images matched using the L1 metric. These results suggest that, in the domain of natural images of the kind we have used, the L1 metric may better capture human notions of image similarity.

Process Variability in Micro-Embossing

A promising technique for the large-scale manufacture of micro-fluidic devices and photonic devices is hot embossing of polymers such as PMMA. Micro-embossing is a deformation process where the workpiece material is heated to permit easier material flow and then forced over a planar patterned tool. While there has been considerable, attention paid to process feasibility very little effort has been put into production issues such as process capability and eventual process control. In this paper, we present initial studies aimed at identifying the origins and magnitude of variability for embossing features at the micron scale in PMMA. Test parts with features ranging from 3.5- 630 µm wide and 0.9 µm deep were formed. Measurements at this scale proved very difficult, and only atomic force microscopy was able to provide resolution sufficient to identify process variations. It was found that standard deviations of widths at the 3-4 µm scale were on the order of 0.5 µm leading to a coefficient of variation as high as 13%. Clearly, the transition from test to manufacturing for this process will require understanding the causes of this variation and devising control methods to minimize its magnitude over all types of parts.