Development of a platform for precise color identification

食品/农业部门是世界上最大的产业，占全球GDP的10%，约5万亿美元。 食品检验是一个数百万美元的增长行业，特别是对全球食品安全和质量检测的关注不断升级。 食品等产品的颜色和外观对消费者的偏好和选择有着深刻的影响，并根据产品的质量和安全性形成了他/她购买决定的基础。同时，颜色感知因个体而异，也取决于照明。因此，需要在生产过程中快速、连续地监测食品颜色，同时能够客观地量化其颜色，以便能够实时拒绝质量较低的产品。Sightline Process Control从事食品检测系统的制造业务。该公司拥有强大的市场份额（仅在美国就超过40%），并拥有麦当劳等客户。然而，为了保持领先的市场和适应不断变化的客户需求，公司必须增加额外的能力，它的产品，例如，以精确地确定食品颜色。 Algonquin学院和Sightline Process Control Inc.之间目前的合作项目。将开发一个atform/方法，使公司制造的食品检测系统，以确定食品颜色独立于特定的系统，照明和其他条件。这将通过“编织”颜色识别算法/软件开发的阿尔冈琴学院与现有的软件的大小/形状表征的视线食品检测系统，运行测试的稳定性，可重复性和一致性在现场/工业条件和调试的问题，同时获取统计数据的平台性能。 开发的平台将帮助公司将其食品检测系统的能力扩展到一个新的层面，实现最先进的质量控制系统。

Food/agriculture sector is the world's biggest industry comprising 10% of global GDP, or ~$5 trillion. Food inspection is a ultimillion $ growing industry especially with escalating concerns regarding the global food safety and quality testing. Color and appearance of products such as food have a deep influence on consumer preferences and choices and form a basis for his/her buying decision based on quality and safety of the product. At the same time, color perception varies among ndividuals and also depends on illumination. Consequently, there is a need for fast, continuous monitoring of food color during production while being able to objectively quantify its color in order to be able to reject in real-time the lower quality products. Sightline Process Control is in the business of manufacturing food inspection systems. The company has a strong market hare (>40% in USA alone) and have customers such as McDonald's. However in order to keep ahead of the market and dapt to evolving client needs the company must add additional capabilities to it's products e.g. to precisely determine food color. The present collaborative project between Algonquin College and Sightline Process Control Inc. will develop a atform/methodology enabling the company manufactured food inspection systems to determine the food color independent n specific system, illumination and other conditions. This will be achieved by "weaving in" color recognition algorithms/software developed by Algonquin College with the existing software for size/shape characterization in the Sightline food inspection ystems, running tests for stability, repeatability and consistency in field/industrial conditions and debugging the problems while acquiring statistical data on the platform performance. The developed platform will help the company to extend the apabilities of its food inspection systems into a new dimension on the road to implementation of state-of-art quality control systems.