S. Toemoe et al., LEARNING-BASED METHOD TO RECOGNIZE AND LOCALIZE GLASSWARE USING LASERRANGE IMAGES, Image and vision computing, 14(2), 1996, pp. 131-134
Citations number
9
Categorie Soggetti
Computer Sciences, Special Topics",Optics,"Engineering, Eletrical & Electronic","Computer Science Artificial Intelligence","Computer Science Software Graphycs Programming","Computer Science Theory & Methods
A system that can be trained to recognize and localize glassware locat
ed on a workbench using laser range images is described. The training
data consists of laser range images of objects of known classification
. The image is preprocessed to isolate a box of pixels corresponding t
o the object, and then the box is given as an input to a neural networ
k. The range readings from the laser range system deviate significantl
y from the actual distances to the glassware, and consequently a surfa
ce fit to the readings has very little resemblance to the actual glass
ware surface. Thus, the straightfoward method of fitting a surface to
the images and matching it with the surface of known glassware is not
feasible. A first version of the system has been developed based on a
system of perceptrons, and the tests have been successful on the image
s taken by a PERCEPTRON P5000 laser range finder.