The Experts below are selected from a list of 18111 Experts worldwide ranked by ideXlab platform
Da-wen Sun - One of the best experts on this subject based on the ideXlab platform.
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Multi-classification of Pizza using computer vision and support vector machine
Journal of Food Engineering, 2008Co-Authors: Da-wen SunAbstract:The classification of Pizza base, sauce spread and topping is highly sensitive to human error for its subjective and inconsistent nature. Image processing techniques combined with machine learning provide an objective and consistent way to accomplish this task. By using a combination of several binary classifiers, support vector machine (SVM) is a state-of-the-art learning algorithm for multi-classification of Pizza base, sauce spread, and topping. With the selected features as input, the one-versus-one and directed acyclic graph (DAG) methods achieved 89.17% and 88.33% multi-classification accuracy respectively for Pizza base, both 87.5% for Pizza sauce spread, and 80.83% and 80.00%, respectively for Pizza topping. The results showed that the computer vision systems developed had a great potential to assist in the automatic multi-classification of Pizza base, sauce spread, and topping.
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Shape extraction and classification of Pizza base using computer vision
Journal of Food Engineering, 2004Co-Authors: Da-wen SunAbstract:The quality of Pizza base should be determined before further processing. However such classification is highly sensitive to human error. Image processing techniques can be used to extract shape features from digital images of Pizza bases. The support vector machine (SVM) is the state-of-the-art classification technique and is capable of learning in high-dimensional feature space with less training data. In this paper, an algorithm for the shape extraction of Pizza base and a new classification algorithm based on Fourier transform and SVM for shape grading of Pizza bases are presented. The experiments showed that 86.7% classification accuracy was achieved with a linear SVM classifier, 95.0% with a polynomial SVM classifier, and 98.3% with a Gaussian radial basis function SVM classifier. The computer vision system developed has a great potential to assist in the automation of Pizza base classification.
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Pizza quality evaluation using computer vision: Part 1. Pizza base and sauce spread
Journal of Food Engineering, 2003Co-Authors: Da-wen Sun, Tadhg BrosnanAbstract:The growth in the popularity and consumption of Pizzas has led to the need for automated quality inspection, so as to maintain confidence and increase production efficiency. In the current research the use of computer vision for inspection of Pizza base and tomato sauce spread quality was investigated. Twenty Pizza bases were analysed for base area, spatial ratio I (SRI), spatial ratio II (SRII), and circularity. For the measurement of the sauce spread characteristics based on 25 samples, the indexes taken were sauce area and heavy area percentage; a fuzzy logic system was then developed to classify the sauce spread samples into classes of acceptable and defective quality. The base area analysis gave a classification error of 13% when compared to human assessment. The experimental results for the sauce spread analysis show that by using computer vision in conjunction with fuzzy logic a classification accuracy of 92% can be achieved.
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Inspecting Pizza topping percentage and distribution by a computer vision method
Journal of Food Engineering, 2000Co-Authors: Da-wen SunAbstract:Topping percentage and distribution are two major features in the quality inspection of Pizzas. The extraction of these features highly depends on the segmentation quality of Pizza images. However, complex visual features and wide varieties of Pizzas make the segmentation task difficult. Traditional segmentation methods are found only partly suitable for most Pizza images. Therefore, a new segmentation method was developed by using the region-based segmentation as a dominant method and combining the strengths of both thresholding and edge-based segmentation methods. For evaluating the evenness of topping distribution, a practical method of dividing a Pizza image into several equal-area partitions was developed. The experimental results show that the computer vision method developed is suitable for many different types of Pizzas with an accuracy of over 90% for measuring topping exposure percentage and distribution.
Barry M Popkin - One of the best experts on this subject based on the ideXlab platform.
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increased portion sizes from energy dense foods affect total energy intake at eating occasions in us children and adolescents patterns and trends by age group and sociodemographic characteristics 1977 2006
The American Journal of Clinical Nutrition, 2011Co-Authors: Carmen Piernas, Barry M PopkinAbstract:Background: Larger portion sizes of foods and beverages could affect overall energy intake at meals and promote overeating. Objective: We investigated trends in portion sizes of energy-dense foods and energy intakes at eating occasions in US children and adolescents. Design: Four US nationally representative surveys from 1977 to 2006 were analyzed (n = 31,337). We measured trends in portion sizes (kcal, g, and mL) of selected foods [sugar-sweetened beverages (SSBs), salty snacks, desserts, French fries, burgers, Pizzas, and Mexican fast foods] and energy intake (kcal) at eating occasions during which selected foods were consumed. Trends were reported by age group (2–6-, 7–12-, and 13–18-y-olds), sex, and socioeconomic status. Results: In 2003–2006, the selected foods accounted for 38% of daily energy intake in 13–18-y-olds, 35% of the daily energy intake in 7–12-y-olds, and 28% of the daily energy intake in 2–6-y-olds. In all age groups, larger portion sizes of Pizza coincided with higher energy intakes at eating occasions during which Pizzas were consumed. In 7–12- and 13–18-y-olds, higher energy intakes at meals coincided with larger portion sizes of SSBs, French fries, or salty snacks. In all age groups, nonsignificant larger portions of Mexican fast foods were related to higher energy intakes at meals. Adolescent boys consumed larger portion sizes of the selected foods and had higher energy intakes at meals for all periods than did girls (P , 0.01). The percentage of kilocalories from Pizza within a meal increased more sharply in non-Hispanic African Americans, in Hispanics, and in the group with a low household education than in the other groups. Conclusions: Adolescents are more susceptible to increased portion sizing than are younger children. The group of non-Hispanic African Americans and Hispanics and individuals with a lower education represents key concerns for public health policies. Am J Clin Nutr 2011;94:1324–32.
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food portion patterns and trends among u s children and the relationship to total eating occasion size 1977 2006
Journal of Nutrition, 2011Co-Authors: Carmen Piernas, Barry M PopkinAbstract:Food and beverage portion sizes are related to childhood obesity. We examined trends in food portion sizes and the association with total meal sizes among U.S. children. We selected children 2- to 18-y-old (n = 31,337) from 4 nationally representative surveys of food intake between 1977–1978 and 2003–2006. We assessed portion sizes (kcal and g) of selected key foods (soft/fruit drinks, salty snacks, desserts, French fries, burgers, Pizzas, Mexican fast foods, and hot dogs), the total energy from eating occasions that included key foods, and portion sizes of the selected key foods by source (stores, restaurants, and fast-food locations). These foods represented over one-third of children’s energy intake in 2003–2006. Portion sizes increased significantly over the 30-y period and increases in Pizza were particularly pronounced in the last decade [+176 kcal (736 kJ). Energy from eating occasions including Pizzas and soft drinks increased, as did the proportion of energy from these foods in an eating occasion. Hamburgers and cheeseburgers increased in portion size and eating occasion size, but the proportion of these foods in the total eating occasions did not increase. Portion sizes of other key foods increased, although the total energy from eating events that included them remained constant (e.g. Mexican fast-foods, French fries, fruit drinks) or decreased (e.g. salty snacks, desserts). Portion sizes increased across all food sources (stores, restaurants, and fast foods) for soft drinks and Pizzas but only at fast-food locations for French fries. Portion sizes continue to grow for selected foods. Fast-food chains appear to be linked with less healthful portion size increases for selected foods.
Biagio Morrone - One of the best experts on this subject based on the ideXlab platform.
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Why not Using Electric Ovens for Neapolitan Pizzas? A Thermal Analysis of a High Temperature Electric Pizza Oven☆
Energy Procedia, 2016Co-Authors: Mena Ciarmiello, Biagio MorroneAbstract:Abstract Neapolitan Pizza should be exclusively baked in wood-ovens with high temperatures. Despite the high quality of cooking provided, combustion products may adversely affect indoor and outdoor air quality. This paper focuses on thermal performances of an electric oven for Neapolitan Pizzas designed to obtain cooking characteristics similar to the wood-fired ovens. A three-dimensional numerical model has been developed for unsteady and steady conditions, using a CFD approach. The temperature fields and profiles of walls and Pizzas, for some meaningful examined cases with different radiative wall emissivity, are reported to verify the quality of oven thermal performances.
Carmen Piernas - One of the best experts on this subject based on the ideXlab platform.
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increased portion sizes from energy dense foods affect total energy intake at eating occasions in us children and adolescents patterns and trends by age group and sociodemographic characteristics 1977 2006
The American Journal of Clinical Nutrition, 2011Co-Authors: Carmen Piernas, Barry M PopkinAbstract:Background: Larger portion sizes of foods and beverages could affect overall energy intake at meals and promote overeating. Objective: We investigated trends in portion sizes of energy-dense foods and energy intakes at eating occasions in US children and adolescents. Design: Four US nationally representative surveys from 1977 to 2006 were analyzed (n = 31,337). We measured trends in portion sizes (kcal, g, and mL) of selected foods [sugar-sweetened beverages (SSBs), salty snacks, desserts, French fries, burgers, Pizzas, and Mexican fast foods] and energy intake (kcal) at eating occasions during which selected foods were consumed. Trends were reported by age group (2–6-, 7–12-, and 13–18-y-olds), sex, and socioeconomic status. Results: In 2003–2006, the selected foods accounted for 38% of daily energy intake in 13–18-y-olds, 35% of the daily energy intake in 7–12-y-olds, and 28% of the daily energy intake in 2–6-y-olds. In all age groups, larger portion sizes of Pizza coincided with higher energy intakes at eating occasions during which Pizzas were consumed. In 7–12- and 13–18-y-olds, higher energy intakes at meals coincided with larger portion sizes of SSBs, French fries, or salty snacks. In all age groups, nonsignificant larger portions of Mexican fast foods were related to higher energy intakes at meals. Adolescent boys consumed larger portion sizes of the selected foods and had higher energy intakes at meals for all periods than did girls (P , 0.01). The percentage of kilocalories from Pizza within a meal increased more sharply in non-Hispanic African Americans, in Hispanics, and in the group with a low household education than in the other groups. Conclusions: Adolescents are more susceptible to increased portion sizing than are younger children. The group of non-Hispanic African Americans and Hispanics and individuals with a lower education represents key concerns for public health policies. Am J Clin Nutr 2011;94:1324–32.
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food portion patterns and trends among u s children and the relationship to total eating occasion size 1977 2006
Journal of Nutrition, 2011Co-Authors: Carmen Piernas, Barry M PopkinAbstract:Food and beverage portion sizes are related to childhood obesity. We examined trends in food portion sizes and the association with total meal sizes among U.S. children. We selected children 2- to 18-y-old (n = 31,337) from 4 nationally representative surveys of food intake between 1977–1978 and 2003–2006. We assessed portion sizes (kcal and g) of selected key foods (soft/fruit drinks, salty snacks, desserts, French fries, burgers, Pizzas, Mexican fast foods, and hot dogs), the total energy from eating occasions that included key foods, and portion sizes of the selected key foods by source (stores, restaurants, and fast-food locations). These foods represented over one-third of children’s energy intake in 2003–2006. Portion sizes increased significantly over the 30-y period and increases in Pizza were particularly pronounced in the last decade [+176 kcal (736 kJ). Energy from eating occasions including Pizzas and soft drinks increased, as did the proportion of energy from these foods in an eating occasion. Hamburgers and cheeseburgers increased in portion size and eating occasion size, but the proportion of these foods in the total eating occasions did not increase. Portion sizes of other key foods increased, although the total energy from eating events that included them remained constant (e.g. Mexican fast-foods, French fries, fruit drinks) or decreased (e.g. salty snacks, desserts). Portion sizes increased across all food sources (stores, restaurants, and fast foods) for soft drinks and Pizzas but only at fast-food locations for French fries. Portion sizes continue to grow for selected foods. Fast-food chains appear to be linked with less healthful portion size increases for selected foods.
D M Barbano - One of the best experts on this subject based on the ideXlab platform.
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a model of mozzarella cheese melting and browning during Pizza baking
Journal of Dairy Science, 1998Co-Authors: M A Rudan, D M BarbanoAbstract:Shreds of full fat Mozzarella cheese usually melt, fuse, and form light brown blisters, but fat-free or lower fat Mozzarella cheese shreds have limited melt and fusion and become scorched during Pizza baking in commercial food service Pizza ovens. Why is the functionality so different? Our results indicate that dehydration of the shred surface and subsequent skin formation are the critical events during Pizza baking that limit melting and induce scorching of fat-free and lower fat Mozzarella cheese during Pizza baking. When skin formation is prevented by lightly coating fat-free (<0.25% fat) and lower fat Mozzarella cheese (6 to 9% fat) shred surfaces with a hydrophobic material (ca. 0.9 g vegetable oil/100 g cheese) prior to Pizza baking, melting and browning of these cheeses were demonstrated to be similar to those of full fat Mozzarella cheese (21% fat). Therefore, fat within the interior microstructure of the cheese was not necessary to achieve the proper functionality of fat-free and lower fat Mozzarella cheeses during Pizza baking. A model is proposed to describe the time series of events occurring during Pizza baking.
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A model of Mozzarella cheese melting and browning during Pizza baking
Journal of Dairy Science, 1998Co-Authors: M A Rudan, D M BarbanoAbstract:Shreds of full fat Mozzarella cheese usually melt, fuse, and form light brown blisters, but fat-free or lower fat Mozzarella cheese shreds have limited melt and fusion and become scorched during Pizza baking in commercial food service Pizza ovens. Why is the functionality so different? Our results indicate that dehydration of the shred surface and subsequent skin formation are the critical events during Pizza baking that limit melting and induce scorching of fat-free and lower fat Mozzarella cheese during Pizza baking. When skin formation is prevented by lightly coating fat-free (
