Publications by Costantino Grana

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This paper proposes the use of an approach of video transcoding driven by the video content and providedwith the adaptive quantization of MPEG standards.Computer vision techniques can extract semanticsfrom videos according with user's interests: the videosemantics is exploited to adapt the video in order tomeet the device's capabilities and the user'srequirements and preserve the best quality possible. Well assessed video analysis techniques are used to segment the video into objects grouped in classes ofrelevance to which the user can assign a weight proportional to their relevance. This weight is used todecide the quantization values to be applied in theMPEG-2 encoding to each macroblock. A modified version of the PSNR (Peak Signal-to-Noise Ratio) is used as performance metric and comparativeevaluation is reported with respect to other codingstandards such as JPEG, JPEG 2000, (basic) MPEG-2, and MPEG-4. Experimental results are provided on different situations, one indoor and oneoutdoor. Keywords:Videotranscoding, adaptive quantization, motion detection

This work presents a novel people tracking approach, able to cope with frequent shape changes and large occlusions. In particular, the tracks are described by means of probabilistic masks and appearance models. Occlusions due to other tracks or due to background objects and false occlusions are discriminated. The tracking system is general enough to be applied with any motion segmentation module, it can track people interacting each other and it maintains the pixel assignment to track even with large occlusions. At the same time, the update model is very reactive, so as to cope with sudden body motion and silhouette's shape changes. Due to its robustness, it has been used in many experiments of people behavior control in indoor situations.

Atypical nevi share some dermoscopic features with early melanoma, and computer elaboration of digital images could represent a useful support to diagnosis. The aim of our study was to automatically assess colors in atypical nevi, and to compare the data with those referring to clearly benign nevi and melanomas. Dermoscopic images of 459 melanocytic lesions, referring to 76 atypical nevi, 288 clearly benign nevi and 95 melanomas, were acquired by means of a digital videomicroscope (Videocap 100, DS-Medica, Italy) employing a 20-fold magnification. An image analysis program, based on an approach, which shares some similarities with the human perception of colors, was employed. For the evaluation of colors in melanocytic lesion images, the identification of the six main color groups (black, dark brown, light brown, red, white and blue-gray) and the numerical description of color areas were obtained. Black, white and blue-gray were more frequently found in atypical nevi than in clearly benign nevi, but less frequently than in melanomas. Color area values significantly differed between the three groups, showing increasing irregularity in color distribution from benign lesions to atypical nevi and melanomas. The clinical–morphological interpretation of the numerical data, based on the mathematical description of the aspect and distribution of different color areas in different lesion types may contribute to the characterization of atypical nevi and their distinction from melanomas.

The assessment of asymmetry is essential for melanoma (MM) diagnosis, both when using a heuristic approach and when employing semiquantitative methods on dermoscopic images. The aim of our study was to develop and validate a software for assessment of asymmetry in melanocytic lesion images, based on evaluation of color symmetry, and to compare the automatic evaluation to the one performed by human observers. An image analysis program enabling the numerical assessment of asymmetry in melanocytic lesions, based on evaluation and comparison of RGB color components inside image color blocks, was employed on 459 videomicroscopic digital images, referring to 95 melanomas (MMs), 76 atypical nevi (AN) and 288 clearly benign nevi (BN). Clinical evaluation of asymmetry on dermoscopic images was performed on the same image set employing a 0–1 scoring system. Asymmetry judgement was expressed by the clinicians for 12.8% of BN, 44.7% of AN, and for 64.2% of MMs, whereas the computer identified 6.9% of BN, 27.6% of AN, and 87.4% of MMs as asymmetric. Sensitivity and specificity of clinical judgement were 64.2 and 80.5%, respectively, whereas for computer evaluation, a sensitivity of 87.5% and a specificity of 85.7% were obtained. Numerical parameters (mean RGB distance, variance and maximum distance) referring to MMs were significantly higher both with respect to BN and AN. This innovative method for automatic asymmetry evaluation, based on the mathematical description of color distribution in different image blocks, provides numerical parameters for employment in computer-aided melanoma diagnosis.

Confocal reflectance microscopy (CRM) enables the in-vivo observation of the skin at a nearly histologic resolution. Since melanin represents a strong source of contrast, this technique appeared particularly indicated for the study of melanocytic lesions. Cytological and architectural features of melanocytic skin lesions were studied on 25 melanomas and 50 atypical melanocytic nevi employing CRM (Vivascope 1000, Lucid Inc., USA) and digital dermoscopy (Videocap 200, DS-Mediroup, Italy). All lesions were excised for diagnostic confirmation. Some differences in CRM features were observed between benign and malignant lesions: in melanocytic nevi, cells were usually round to oval, mainly located in the basal layers or clustered into nests within the papillary dermis. Melanomas were characterized by numerous large cells within the superficial layers of the epidermis, suggesting a pagetoid fashion, and by cells polymorphic in size and shape mainly located in the basal layer, sometimes interrupted by small dermal papillae irregularly distributed throughout the lesion, owing to disarrangement of the normal architecture of the rete ridges. Moreover, large irregular cells with refractive cytoplasm and eccentric dark nucleus infiltrating dermal papilla and cell clusters with a multilobulated feature constituted by sparse cells or with a cerebriform aspect were specifically observed in melanomas. Although preliminary and based on a limited number of cases, these findings show the potential of this technique for the noninvasive diagnosis of clinically difficult lesions.

People tracking deals with problems of shape changes, self-occlusions and track occlusions due to other interfering tracks and fixed objects that hide parts of the people shape. These problems are more critical in indoor surveillance and in particular in home automation settings, in which the need to merge information obtained form different cameras distributed around the house calls for the integration of reliable data obtained during time. Therefore, tracking algorithms should be carefully tuned to cope with occlusions and shape changes, working not only at pixel level but also at region level. In this work we provide a novel technique for object tracking, based on probabilistic masks and appearance models. Occlusions due to other tracks or due to background objects and false occlusions are discriminated. The classification of occluded regions of the track is exploited in a selective model update. The tracking system is general enough to be applied with any motion segmentation module, it can track people interacting each other and it maintains the pixel to track assignment even with large occlusions. At the same time, the model update is very reactive, so as to cope with sudden body motion and silhouette's shape changes. Due to its robustness, it has been used in different experiments of people behavior control in indoor situations.

Background: Identification of dark areas inside a melanocytic lesion (ML) is of great importance for melanoma diagnosis, both during clinical examination and employing programs for automated image analysis. Objective: The aim of our study was to compare two different methods for the automated identification and description of dark areas in epiluminescence microscopy images of MLs and to evaluate their diagnostic capability. Methods: Two methods for the automated extraction of ´absolute´ (ADAs) and ´relative´ dark areas (RDAs) and a set of parameters for their description were developed and tested on 339 images of MLs acquired by means of a polarized-light videomicroscope. Results: Significant differences in dark area distribution between melanomas and nevi were observed employing both methods, permitting a good discrimination of MLs (diagnostic accuracy = 74.6 and 71.2% for ADAs and RDAs, respectively). Conclusions: Both methods for the automated identification of dark areas are useful for melanoma diagnosis and can be implemented in programs for image analysis. Copyright

The aim of this study was to develop a computerized method for the identification and description of colour areas in melanocytic lesion images based on an approach mimicking the human perception of colours. A colour palette comprising six colour groups (black, dark brown, light brown, blue-grey, red and white) was created by selecting single colour components within melanocytic lesion images acquired using a digital videomicroscope, and was implemented in the image analysis program. For each colour region, the area, the distance from the lesion centroid, the spread, the colour area distribution in the internal and the external part of the lesion, and asymmetries were assessed on 604 melanocytic lesion images in our image database. Black, white and blue-grey colour areas were detected more frequently in melanomas compared with naevi. Moreover, significant differences in colour descriptors were observed for each colour group, showing that colour areas are more unevenly distributed in melanomas compared with naevi. Using a discriminant analysis approach, the extension of dark, white and blue-grey areas and some descriptors of the distribution of the colour areas were identified as the most relevant colour parameters for differentiating between benign and malignant lesions. In conclusion, our automatic procedure breaks down the image into the colour areas used in the clinical examination process, and also supplies a description of their extension and distribution, with parameters that correlate with the clinical concepts of regularity and homogeneity.