Uniformity Evaluation of Temperature Field in an Oven Based on Image Processing

Non-uniform temperature distributions in ovens affect the quality of baked goods and raise concerns regarding food safety. Traditional research on oven performance focuses on the heating mechanisms in simulated ovens and does not involve quantitative analysis of baked goods. This study proposes a model for calculating the uniformity of baked goods based on image processing technology, to quantitatively assess the distribution uniformity of different baked states and digitally express the internal temperature field distribution in the oven. First, the image of the baked goods is captured using a digital camera. Then, it is preprocessed to obtain an image containing only the region showing the baked goods. Subsequently, the simple linear iterative clustering segmentation algorithm is employed to extract the baked states. Finally, a meshing model is applied to calculate the distribution variance of each baked state, and the evaluation index describing the uniformity of the baked goods image is obtained by normalizing the variance in the distribution. The simple linear iterative clustering segmentation algorithm expresses the color features of acquired baked goods images in the form of superpixels. By determining the distribution and proportion of different baked states, the proposed method can qualitatively and quantitatively reflect the spatial distribution of the temperature fields inside the oven corresponding to the baked goods image. This provides a strong basis for further evaluation of the heat distribution field inside the oven.

[1]  Larry D. Hostetler,et al.  The estimation of the gradient of a density function, with applications in pattern recognition , 1975, IEEE Trans. Inf. Theory.

[2]  Pascal Fua,et al.  SLIC Superpixels Compared to State-of-the-Art Superpixel Methods , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Rainer Stiefelhagen,et al.  Measuring and evaluating the compactness of superpixels , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

[4]  Yizong Cheng,et al.  Mean Shift, Mode Seeking, and Clustering , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Zheng Fei,et al.  Method for Evaluating Casing Uniformity of Tobacco Strips Based on Image Processing , 2015 .

[6]  He Ma,et al.  Breast Cancer Classification with Ultrasound Images Based on SLIC , 2019, ArXiv.

[7]  S. Lakshmi,et al.  IJCA Special Issue on “Computer Aided Soft Computing Techniques for Imaging and Biomedical Applications” CASCT, 2010. A study of Edge Detection Techniques for Segmentation Computing Approaches , 2022 .

[8]  Adel Hafiane,et al.  Weeds detection in UAV imagery using SLIC and the hough transform , 2017, 2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA).

[9]  Ioannis Pitas,et al.  Digital Image Processing Algorithms and Applications , 2000 .

[10]  K. M. Pooja,et al.  Image Segmentation: A Survey , 2016 .

[11]  S. Vasuki,et al.  Multiresolution joint bilateral filtering with modified adaptive shrinkage for image denoising , 2016, Multimedia Tools and Applications.

[12]  C. Helen Sulochana,et al.  Image denoising using bilateral filter in subsampled pyramid and nonsubsampled directional filter bank domain , 2016, J. Intell. Fuzzy Syst..

[13]  Josse De Baerdemaeker,et al.  Computational fluid dynamics modelling and validation of the isothermal airflow in a forced convection oven , 2000 .

[14]  Wei Jiang A Glass Uniformity Inspection System Based on Image Processing , 2004 .

[15]  Joe W Button,et al.  Unified Imaging Approach for Measuring Aggregate Angularity and Texture , 2000 .

[16]  Nantawan Therdthai,et al.  Recent Advances in the Studies of Bread Baking Process and Their Impacts on the Bread Baking Technology , 2003 .

[17]  Jacek Smolka,et al.  Improved 3-D temperature uniformity in a laboratory drying oven based on experimentally validated CFD computations. , 2010 .

[18]  S. Indu,et al.  Local Enhancement of SLIC Segmented Underwater Images using Gray World based Algorithm , 2017, 2017 Ninth International Conference on Advances in Pattern Recognition (ICAPR).

[19]  C. Anandharamakrishnan,et al.  Computational fluid dynamics (CFD) modeling of an electrical heating oven for bread-baking process , 2010 .