A Concept for Camera-based Classification of Load Carriers

Download statistics - Document (COUNTER):

Holm, D.-M.; Fottner, J.: A Concept for Camera-based Classification of Load Carriers. In: Herberger, D.; Hübner, M. (Eds.): Proceedings of the Conference on Production Systems and Logistics : CPSL 2021. Hannover : publish-Ing., 2021, S. 23-31. DOI: https://doi.org/10.15488/11268

Selected time period:

year: 
month: 

Sum total of downloads: 67




Thumbnail
Abstract: 
Due to growing environmental awareness, the Circular Economy and in particular the concept of ReverseLogistics (RL) are more and more becoming the focus of industry, yielding ecological as well as economicadvantages. However, the successful implementation of the concepts requires that several challenges be met.One of the most common challenges is the lack of information within RL. One proposed solution is to usemore Automatic Identification Systems (Auto-ID) to track returning goods and close the information gapsbetween RL participants. Currently available identification systems are often limited in their field ofapplication, as they can be very expensive, require a huge change in current logistics processes or sufferfrom physical characteristics, such as electromagnetic absorption or limited visual contact. With this paper,we introduce our novel concept for load carrier classification and quantification using Time-of-Flight (ToF)cameras in combination with color images, beginning with a general overview of the system architectureand process structure. This is followed by an in-depth analysis of the process steps, starting with triggeringcamera records followed by image pre-processing, classification and finally a quantification of the loadedcargo.
License of this version: CC BY 3.0 DE
Document Type: bookPart
Publishing status: publishedVersion
Issue Date: 2021
Appears in Collections:Proceedings CPSL 2021
Proceedings CPSL 2021

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 40 59.70%
2 image of flag of United States United States 7 10.45%
3 image of flag of Russian Federation Russian Federation 6 8.96%
4 image of flag of No geo information available No geo information available 2 2.99%
5 image of flag of Japan Japan 2 2.99%
6 image of flag of Egypt Egypt 2 2.99%
7 image of flag of China China 2 2.99%
8 image of flag of Canada Canada 2 2.99%
9 image of flag of Vietnam Vietnam 1 1.49%
10 image of flag of Czech Republic Czech Republic 1 1.49%
    other countries 2 2.99%

Further download figures and rankings:


Hinweis

Zur Erhebung der Downloadstatistiken kommen entsprechend dem „COUNTER Code of Practice for e-Resources“ international anerkannte Regeln und Normen zur Anwendung. COUNTER ist eine internationale Non-Profit-Organisation, in der Bibliotheksverbände, Datenbankanbieter und Verlage gemeinsam an Standards zur Erhebung, Speicherung und Verarbeitung von Nutzungsdaten elektronischer Ressourcen arbeiten, welche so Objektivität und Vergleichbarkeit gewährleisten sollen. Es werden hierbei ausschließlich Zugriffe auf die entsprechenden Volltexte ausgewertet, keine Aufrufe der Website an sich.

Search the repository


Browse