AUTOMATIC IDENTIFICATION SYSTEM FOR RAW POULTRY PORTIONS

Abstract

ABSTRACTIn poultry processing plants, the sorting of raw poultry portions into separate containers prior to packaging is performed mostly by human laborers. This sorting method has two problems: labor cost and health hazard due to possible contamination between raw meat and humans. Therefore, an automated sorting system is required to avoid these problems. In this article, we present an automatic portion identification system that uses image processing and a neural network to identify six different chicken portions that are usually preferred by consumers. The proposed rotational invariant system can identify the cut portions regardless of their orientation with an overall correct identification rate of 97.57%. Potentially, the output of the proposed identification system can be used to move robotic arms to physically separate the identified chicken portions into separate containers.PRACTICAL APPLICATIONSThis work contributes to the development of an automated sorting system for practical use in poultry processing plants. The presented intelligent identification system is the main part of such an automated system. We train the system in this work to recognize the main chicken portions; however, other portions and other poultry birds can also be identified upon including their portion images in the training phase. This work differs from existing systems, in that it relies totally on the shape and coarse texture of a portion, using images as input data, and discards information like weight or size of the portion. Another advantage is the elimination of the need for using many birds during the development of the system; in fact, training the system can be achieved using only one bird and its portions.