Article Identification for Inventory List in a Warehouse Environment

From ISLAB/CAISR
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

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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.