Recent computational and analytical studies have shown that cellular fabric-as embodied by average cell size, aspect ratio and orientation-is a key indicator of the stresses acting in an embryonic epithelium. Cellular fabric in real embryonic tissues could not previously be measured automatically because the cell boundaries tend to be poorly defined, significant lighting and cell pigmentation differences occur and tissues contain a variety of cell geometries. To overcome these difficulties, four algorithms were developed: least squares ellipse fitting (LSEF), area moments (AM), correlation and axes search (CAS) and Gabor filters (GF). The AM method was found to be the most reliable of these methods, giving typical cell size, aspect ratio and orientation errors of 18%, 0.10 and 7.4 degrees, respectively, when evaluated against manually segmented images. The power of the AM algorithm to provide new insights into the mechanics of morphogenesis is demonstrated through a brief investigation of gastrulation, where fabric data suggest that key gastrulation movements are driven by epidermal tensions circumferential to the blastopore.

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A technique to improve the positional accuracy of mobile ground-based LIDAR systems is proposed. Terrapoint's TITAN TM system scans the same objects at different times, so by aligning scans, any drift over time can be estimated. This paper describes a simple way of tessellating the scanned data into segments based on the vehicle's path. Principal Components Analysis is then used to estimate how well pairs of segments will align when registered with an Iterative Closest Point algorithm. The results show that this analysis does indeed find segments which are likely to register well. Finally a more formal method to analyze the results is proposed, to better determine the quality of the registration so that it can be used to improve the position estimate for the LIDAR system.Canadian Conference on Computer and Robot Vision 978-0-7695-3153-3/08 $25.00