An Intelligent Quantitative Evaluation Method of Baked Goods Quality Based on Vision

The uneven temperature field in the oven will not only affect the beauty of baked goods, but also directly related to food safety. The quantitative evaluation method of baking quality based on vision is a non-contact standardized test method, and the results can provide a basis for the design optimization of internal temperature field of household oven. However, the mapping relationship between oven temperature field and baking state of baked goods is uncertain. Therefore, it is necessary to design a method to detect the baking quality of the baked goods. By judging the baking state of the baked goods under a certain temperature field, the performance of the temperature field produced by the oven can be obtained. In this paper, the proposed intelligent quantitative evaluation method of baking quality includes four parts: 1. Designing the cabinet of baking image acquisition equipment to capture the baking image under the condition of consistent light source; 2. Based on HSV - LBP feature, the light weight baked goods segmentation algorithm can obtain the pure baked goods region; 3. The surface consistency of baked goods was evaluated based on multi-scale variance; 4. The baking state of the baked goods was obtained based on the evaluation index of the baking state of the baked goods in Lab color space. The proposed method was used to evaluate the baking state of two representative baked goods, toast and cookies, and the results were compared with the manual test results, which proved the effectiveness and robustness of the proposed method.