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。食品检验是一个价值数百万美元的增长行业，尤其是随着人们对全球食品安全和质量检测的担忧不断升级。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，是消费者根据产品的质量和安全做出购买决定的依据。同时，色彩感知因人而异，也取决于光照。因此，需要在生产过程中对食品颜色进行快速、连续的监测，同时能够客观地量化其颜色，以便能够实时拒绝低质量的产品。视线过程控制是制造食品检验系统的业务。该公司拥有强大的市场份额（仅在美国就有40%的市场份额），并拥有麦当劳等客户。然而，为了保持市场领先地位并适应不断变化的客户需求，公司必须为其产品增加额外的功能，例如精确确定食品颜色。目前，阿尔冈昆学院和视线过程控制公司之间的合作项目将开发一个平台/方法，使公司制造的食品检验系统能够独立于特定系统、照明和其他条件下确定食品颜色。这将通过将Algonquin学院开发的颜色识别算法/软件与Sightline食品检测系统中现有的尺寸/形状表征软件“编织”在一起来实现，在现场/工业条件下运行稳定性、可重复性和一致性测试，并在获取平台性能统计数据的同时调试问题。开发的平台将帮助公司在实施最先进的质量控制系统的道路上，将其食品检验系统的能力扩展到一个新的维度。

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.