This paper presents a new efficient method of waste paper sorting system using simple image processing technique. The primary challenge in the recycling of paper is to obtain raw material with the highest purity. Highly sorted paper stream will facilitate high quality end product, and save processing chemicals and energy. Automated paper sorting systems offer significant advantages over human inspection from fatigue, throughput, speed and accuracy point of view. From 1932 to 2008, different mechanical and optical paper sorting methods have been developed to fill up the demand of paper sorting. Still many countries including Malaysia, waste papers are sorted into different grades using manual sorting system. Due to inadequate throughput and some major drawbacks of mechanical paper sorting systems, the popularity of optical paper sorting systems is increased. This paper attempts to develop a learning based vision sensing system that will be able to separate the different grades of paper using statistical reasoning. The remarkable achievement obtained from the proposed method is the result of identification and versatility for all grades of paper just using only one sensor, which is the best among the prevailing techniques of automated paper sorting systems. © EuroJournals Publishing, Inc. 2009.
|Number of pages||85|
|Journal||European Journal of Scientific Research|
|Publication status||Published - 01 Jan 2009|
Rahman, M. O., Hannan, M. A., Scavino, E., Hussain, A., & Basri, H. (2009). An efficient paper grade identification method for automatic recyclable waste paper sorting. European Journal of Scientific Research, 96-103.