Article Identification for Inventory List in a Warehouse Environment

Title Article Identification for Inventory List in a Warehouse Environment
Summary Article Identification for Inventory List in a Warehouse Environment
Keywords image segmentation, object recognition, classification, computer vision
TimeFrame Start: February 2014, End: June 2014
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Prerequisites Image Analysis, Machine Learning, programming skill
Author Yang Gao
Supervisor Björn Åstrand, Saeed Gholami Shahbandi
Level Master
Status Ongoing

For the purpose of intelligent warehouse development, an important step is a better understanding of the environment. One of the elements that provide this better understanding is an inventory list of articles. Automatic construction of an inventory list in a warehouse environment requires detection, identification, quantity estimation and localization of stored articles from images. These images are stored via a camera mounted on lift-trucks operating in a real warehouse.

Research Question: How to employ environmental structure (pallets or pallet rack cell) to handle challenging image segmentation in a highly cluttered scene is one of the questions that should be answered. Fast features description for object recognition in a warehouse environment is another challenge required for handling a sequence of images.

Work package 1: image preprocessing (system setup) Work package 2: object detection (image segmentation) Work package 3: object recognition (classification) Work package 4: quantity estimation (bonus part)

Deliverable: an implementation and demonstration of a developed method for listing articles appearing in an image sequence.