Support vector machines for automated classification of plastic bottles

Shahrani Shahbudin, Aini Hussain, Dzuraidah Abd. Wahab, Mohd. Marzuki Mustafa, Suzaimah Ramli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

Many recycling activities adopt manual sorting for plastic recycling that relies on plant personnel who visually identify and pick plastic bottles as they travel along the conveyor belt. These bottles are then sorted into the respective containers. Manual sorting may not be a suitable option for recycling facilities of high throughput. It has also been noted that the high turnover among sorting line workers had caused difficulties in achieving consistency in the plastic separation process. As a result, an intelligent system for automated sorting is greatly needed to replace manual sorting system. The core components of machine vision for this intelligent sorting system is the image recognition and classification.[3]Therefore, in this work, an automated classification of plastic bottles based on the extraction of best feature vectors to represent the type of plastic bottles is performed using the morphological based approach. Morphological operations are used to describe the structure or form of an image. By using the two-dimensional description of plastic bottle silhouettes, edge detection of the object silhouette is performed followed by the erosion process. This procedure can be considered as two stages; a) a feature vector is extracted from the analysis of morphological operation and structure element used and b) a classification technique is applied to that input vector in order to provide a meaningful categorization of the data content. In this study, Support Vector Machines (SVM) was employed merely to classify the image of two groups of plastic bottles namely polyethyleneterephthalate (PET) and non-PET. Additionally, for detailed classification task, the pattern of decision boundary for classification of extracted feature vectors based on morphological approach is also illustrated. Furthermore, the optimal features for input to SVM classifier is identified.The initial results indicate that the performance of the SVM in terms of classification accuracy is more than 90%.

Original languageEnglish
Title of host publicationProceedings - CSPA 2010: 2010 6th International Colloquium on Signal Processing and Its Applications
DOIs
Publication statusPublished - 2010
Event2010 6th International Colloquium on Signal Processing and Its Applications, CSPA 2010 - Melaka
Duration: 21 May 201023 May 2010

Other

Other2010 6th International Colloquium on Signal Processing and Its Applications, CSPA 2010
CityMelaka
Period21/5/1023/5/10

Fingerprint

Plastic bottles
Sorting
Support vector machines
Recycling
Image recognition
Image classification
Bottles
Edge detection
Intelligent systems
Computer vision
Containers
Erosion
Classifiers
Throughput
Personnel
Plastics

Keywords

  • Morphological operations
  • Non-PET
  • PET
  • Plastic bottle
  • Support vector machines (SVM)

ASJC Scopus subject areas

  • Artificial Intelligence
  • Signal Processing
  • Control and Systems Engineering

Cite this

Shahbudin, S., Hussain, A., Abd. Wahab, D., Mustafa, M. M., & Ramli, S. (2010). Support vector machines for automated classification of plastic bottles. In Proceedings - CSPA 2010: 2010 6th International Colloquium on Signal Processing and Its Applications [5545265] https://doi.org/10.1109/CSPA.2010.5545265

Support vector machines for automated classification of plastic bottles. / Shahbudin, Shahrani; Hussain, Aini; Abd. Wahab, Dzuraidah; Mustafa, Mohd. Marzuki; Ramli, Suzaimah.

Proceedings - CSPA 2010: 2010 6th International Colloquium on Signal Processing and Its Applications. 2010. 5545265.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shahbudin, S, Hussain, A, Abd. Wahab, D, Mustafa, MM & Ramli, S 2010, Support vector machines for automated classification of plastic bottles. in Proceedings - CSPA 2010: 2010 6th International Colloquium on Signal Processing and Its Applications., 5545265, 2010 6th International Colloquium on Signal Processing and Its Applications, CSPA 2010, Melaka, 21/5/10. https://doi.org/10.1109/CSPA.2010.5545265
Shahbudin S, Hussain A, Abd. Wahab D, Mustafa MM, Ramli S. Support vector machines for automated classification of plastic bottles. In Proceedings - CSPA 2010: 2010 6th International Colloquium on Signal Processing and Its Applications. 2010. 5545265 https://doi.org/10.1109/CSPA.2010.5545265
Shahbudin, Shahrani ; Hussain, Aini ; Abd. Wahab, Dzuraidah ; Mustafa, Mohd. Marzuki ; Ramli, Suzaimah. / Support vector machines for automated classification of plastic bottles. Proceedings - CSPA 2010: 2010 6th International Colloquium on Signal Processing and Its Applications. 2010.
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