Sm. Prabhu et Dp. Garg, A LABELED OBJECT IDENTIFICATION SYSTEM USING MULTILEVEL NEURAL NETWORKS, Information sciences, applications, 3(2), 1995, pp. 111-126
Citations number
28
Categorie Soggetti
Information Science & Library Science","Computer Science Information Systems
This paper describes the design of a neural network based labeled obje
ct identification system, to be used for product classification at the
final inspection stage of an IBM personal computer manufacturing line
. The objective was to design an identification system using existing
equipment that would provide robust and accurate classification, as we
ll as a simple means for adding new product models to the system. In t
he first stage of the identification system, an image of the product i
s obtained, and the region containing the label is segmented from the
rest of the image. Preprocessing operations are performed to extract t
he region of interest from the segmented image. Normalized and preproc
essed images of the labels are compressed using a fully-connected back
-propagation autoencoder network. Features extracted in this manner ar
e used as inputs to a Learning Vector Quantization (LVQ) network, trai
ned to classify the labels. The system so designed is shown to satisfy
the primary requirements of a typical industrial classification syste
m.