Research Article Open Access

Histogram of Intensity Feature Extraction for Automatic Plastic Bottle Recycling System Using Machine Vision

Suzaimah Ramli, Mohd Marzuki Mustafa, Aini Hussain and Dzuraidah Abdul Wahab

Abstract

Currently, 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. In this research, the overall plastic bottle sorting system is described. Additionally, the feature extraction algorithm used is discussed in detail since it is the core component of the overall system that determines the success rate. The performance of the proposed feature extractions were evaluated in terms of classification accuracy and result obtained showed an accuracy of more than 80%.

American Journal of Environmental Sciences
Volume 4 No. 6, 2008, 583-588

DOI: https://doi.org/10.3844/ajessp.2008.583.588

Submitted On: 30 November 2007 Published On: 31 December 2008

How to Cite: Ramli, S., Mustafa, M. M., Hussain, A. & Wahab, D. A. (2008). Histogram of Intensity Feature Extraction for Automatic Plastic Bottle Recycling System Using Machine Vision . American Journal of Environmental Sciences, 4(6), 583-588. https://doi.org/10.3844/ajessp.2008.583.588

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Keywords

  • Bounding box image
  • region of interest
  • histogram of intensity
  • plastic recycling