Rheological properties of food products are strongly related to their microstructure. Microscopy ... more Rheological properties of food products are strongly related to their microstructure. Microscopy is thus a preferred tool in food research. In food science, microscopy has long been used for visual inspection. Recently, however, quantitative analysis has become the new trend. In spite of this, only a few experts in computer vision are actively involved into image analysis projects, applied to food microscopy. Microscopists tend to use simple tools, without bothering whether they are appropriate for their application. As a consequence, most published work in food science journals lacks scientific rigour, when it comes to analysing images. On the other hand, image analysis experts tend to undervalue microscopists' needs and opinions, which can be surprisingly different from what most people in the computer vision community might think. Drawing upon our experience, we try to highlight microscopists' perspective on image segmentation and, at the same time, show a few examples of collaborative projects that compute interesting measures for the food science community, that do not rely on segmentation accuracy.
Journal of Plastic, Reconstructive & Aesthetic Surgery, 2008
Outcome evaluation in cosmetic and reconstructive surgery of the breast is commonly performed vis... more Outcome evaluation in cosmetic and reconstructive surgery of the breast is commonly performed visually or employing bi-dimensional photography. The reconstructive process in the era of anatomical implants requires excellent survey capabilities that mainly rely on surgeon experience. In this paper we present a set of parameters to unambiguously estimate the shape of natural and reconstructed breast. A digital laser scanner was employed on seven female volunteers. A graphic depiction of curvature of the thoracic surface has been the most interesting result. Further work is required to provide clinical and instrumental validation to our technique.
The surface of milk fat globules consists of a biological membrane rich in polar lipids and glyco... more The surface of milk fat globules consists of a biological membrane rich in polar lipids and glycoproteins. However, high shear stress applied upon homogenization disrupts the membrane and leads to the adsorption of casein micelles, as the major protein fraction of milk. These changes in the interface properties could affect the interactions between native or homogenized milk fat globules and the surrounding protein matrix, at neutral pH and upon acidification. In this study, macroscale rheometry, microscopic observations, nanoscale AFM-based force spectroscopy and physico-chemical analysis were combined to examine the interfacial composition and structure of milk fat globules and to evaluate their interactions with casein micelles. We showed that the surface properties of milk fat globules (biological membrane vs. caseins) and pH govern their interactions with casein micelles. The adhesion between individual fat globules and casein micelles was higher upon homogenization, especially at acid pH where the work of adhesion increased from 3.3 x 10-18 to 14 x 10-18 J for native and homogenized fat globules, respectively. Consequently, casein-coated homogenized fat globules yield stiffer milk acid gels. These findings cast light on the importance of colloidal particle's surface properties and pH on their connectivity with the surrounding matrix, which modulates the bulk microstructure and rheological properties with potential functional consequences, such as milk lipid digestion.
In this chapter, we highlight some of the common pitfalls in the use of image analysis. We show a... more In this chapter, we highlight some of the common pitfalls in the use of image analysis. We show a few examples of how image analysis can be successfully used, possibly in conjunction with sensory analysis and visual observation, to discover interesting properties about food products. Special attention is granted to segmentation, a ubiquitous image processing step, propaedeutic to most quantitative analysis methods. In fact, this is the most critical step of all the image analysis chain and is potentially disastrous for the quality of ...
Supervised learning approaches to image segmentation receive considerable interest due to their p... more Supervised learning approaches to image segmentation receive considerable interest due to their power and flexibility. However, the training phase is not painless, often being long and tedious. Accurate image labelling can take several hours of expert operators' valuable time. User interfaces are often specifically designed to assist the user for the task at hand. This is clearly unfeasible for most application domains. We propose a simple segmentation framework based on classification and supervised incremental learning. A statistical model of pixel classes is learnt by incrementally adding new sample image patches to automatically-learned probability functions. Learning is iterated and refined in a number of steps rather than being executed in a one-shot training phase. We show that one-shot training and incremental labelling tend to produce similar statistical models, as the number of iterations grows. Comparable classification results are thus obtained with considerably less human effort.
Abstract: Computer-aided diagnosis for pre-operative planning and post-operative outcome evaluati... more Abstract: Computer-aided diagnosis for pre-operative planning and post-operative outcome evaluation is widely considered an important topic for next-generation surgery. 3D models of the patients' anatomical structures can be highly valuable in this context. The accuracy of these models is strongly dependent on the classification and segmentation algorithms acting at the very first stage of the modelling chain. A promising class of segmentation algorithms is related to level set methods. Here, we briefly review some applications of level sets to ...
Vector representation of digital images offer a number of advantages over the more common raster ... more Vector representation of digital images offer a number of advantages over the more common raster representation, such as scalability and resolution independence. Many efforts have been addressed to scalable raster representations for photographic imagery for portable applications. However, they lack the flexibility and simplicity of vector representation. Vector graphics is a new and little explored alternative to the more common raster representation. This paper is devoted to outline our experience in the field of vectorialisation of photographic raster images and to highlight ongoing research.
This paper presents a method to optimize the visual quality of JPEG2000-compressed images using a... more This paper presents a method to optimize the visual quality of JPEG2000-compressed images using an adaptive approach to assign more bits to regions in which errors are more visible, maintaining the global bit-rate unchanged.
Rheological properties of food products are strongly related to their microstructure. Microscopy ... more Rheological properties of food products are strongly related to their microstructure. Microscopy is thus a preferred tool in food research. In food science, microscopy has long been used for visual inspection. Recently, however, quantitative analysis has become the new trend. In spite of this, only a few experts in computer vision are actively involved into image analysis projects, applied to food microscopy. Microscopists tend to use simple tools, without bothering whether they are appropriate for their application. As a consequence, most published work in food science journals lacks scientific rigour, when it comes to analysing images. On the other hand, image analysis experts tend to undervalue microscopists' needs and opinions, which can be surprisingly different from what most people in the computer vision community might think. Drawing upon our experience, we try to highlight microscopists' perspective on image segmentation and, at the same time, show a few examples of collaborative projects that compute interesting measures for the food science community, that do not rely on segmentation accuracy.
Journal of Plastic, Reconstructive & Aesthetic Surgery, 2008
Outcome evaluation in cosmetic and reconstructive surgery of the breast is commonly performed vis... more Outcome evaluation in cosmetic and reconstructive surgery of the breast is commonly performed visually or employing bi-dimensional photography. The reconstructive process in the era of anatomical implants requires excellent survey capabilities that mainly rely on surgeon experience. In this paper we present a set of parameters to unambiguously estimate the shape of natural and reconstructed breast. A digital laser scanner was employed on seven female volunteers. A graphic depiction of curvature of the thoracic surface has been the most interesting result. Further work is required to provide clinical and instrumental validation to our technique.
The surface of milk fat globules consists of a biological membrane rich in polar lipids and glyco... more The surface of milk fat globules consists of a biological membrane rich in polar lipids and glycoproteins. However, high shear stress applied upon homogenization disrupts the membrane and leads to the adsorption of casein micelles, as the major protein fraction of milk. These changes in the interface properties could affect the interactions between native or homogenized milk fat globules and the surrounding protein matrix, at neutral pH and upon acidification. In this study, macroscale rheometry, microscopic observations, nanoscale AFM-based force spectroscopy and physico-chemical analysis were combined to examine the interfacial composition and structure of milk fat globules and to evaluate their interactions with casein micelles. We showed that the surface properties of milk fat globules (biological membrane vs. caseins) and pH govern their interactions with casein micelles. The adhesion between individual fat globules and casein micelles was higher upon homogenization, especially at acid pH where the work of adhesion increased from 3.3 x 10-18 to 14 x 10-18 J for native and homogenized fat globules, respectively. Consequently, casein-coated homogenized fat globules yield stiffer milk acid gels. These findings cast light on the importance of colloidal particle's surface properties and pH on their connectivity with the surrounding matrix, which modulates the bulk microstructure and rheological properties with potential functional consequences, such as milk lipid digestion.
In this chapter, we highlight some of the common pitfalls in the use of image analysis. We show a... more In this chapter, we highlight some of the common pitfalls in the use of image analysis. We show a few examples of how image analysis can be successfully used, possibly in conjunction with sensory analysis and visual observation, to discover interesting properties about food products. Special attention is granted to segmentation, a ubiquitous image processing step, propaedeutic to most quantitative analysis methods. In fact, this is the most critical step of all the image analysis chain and is potentially disastrous for the quality of ...
Supervised learning approaches to image segmentation receive considerable interest due to their p... more Supervised learning approaches to image segmentation receive considerable interest due to their power and flexibility. However, the training phase is not painless, often being long and tedious. Accurate image labelling can take several hours of expert operators' valuable time. User interfaces are often specifically designed to assist the user for the task at hand. This is clearly unfeasible for most application domains. We propose a simple segmentation framework based on classification and supervised incremental learning. A statistical model of pixel classes is learnt by incrementally adding new sample image patches to automatically-learned probability functions. Learning is iterated and refined in a number of steps rather than being executed in a one-shot training phase. We show that one-shot training and incremental labelling tend to produce similar statistical models, as the number of iterations grows. Comparable classification results are thus obtained with considerably less human effort.
Abstract: Computer-aided diagnosis for pre-operative planning and post-operative outcome evaluati... more Abstract: Computer-aided diagnosis for pre-operative planning and post-operative outcome evaluation is widely considered an important topic for next-generation surgery. 3D models of the patients' anatomical structures can be highly valuable in this context. The accuracy of these models is strongly dependent on the classification and segmentation algorithms acting at the very first stage of the modelling chain. A promising class of segmentation algorithms is related to level set methods. Here, we briefly review some applications of level sets to ...
Vector representation of digital images offer a number of advantages over the more common raster ... more Vector representation of digital images offer a number of advantages over the more common raster representation, such as scalability and resolution independence. Many efforts have been addressed to scalable raster representations for photographic imagery for portable applications. However, they lack the flexibility and simplicity of vector representation. Vector graphics is a new and little explored alternative to the more common raster representation. This paper is devoted to outline our experience in the field of vectorialisation of photographic raster images and to highlight ongoing research.
This paper presents a method to optimize the visual quality of JPEG2000-compressed images using a... more This paper presents a method to optimize the visual quality of JPEG2000-compressed images using an adaptive approach to assign more bits to regions in which errors are more visible, maintaining the global bit-rate unchanged.
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Papers by Gaetano Impoco