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
DOI : 10.3844/ajessp.2008.583.588
American Journal of Environmental Sciences
Volume 4, Issue 6
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%.
© 2008 Suzaimah Ramli, Mohd Marzuki Mustafa, Aini Hussain and Dzuraidah Abdul Wahab. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.