Gianpiero Di Blasi

Artificial Mosaics by Gradient Vector Flow

In this paper a novel approach for artificial mosaic generation is proposed. Gradient Vector Flow computation together with heuristics to maximise the covered mosaic area are used. The high frequency details are managed in a global way allowing to preserve the mosaic-style also for small ones. Experiments and comparisons with previous works confirm the effectiveness of the proposed algorithm.

SVG Rendering by Watershed Decomposition

This paper presents a novel raster-to-vector technique for digital images by advanced watershed decomposition coupled with some ad-hoc heuristics devoted to obtain high quality rendering of digital photography. The system is composed by two main steps: first, the image is partitioned into homogeneous and contiguous regions using Watershed decomposition. Then, a Scalable Vector Graphics (SVG) representation of such areas is achieved by ad-hoc chain code building. The final result is an SVG file of the image that can be used for the transmission of pictures through Internet using different display systems (PC, PDA, Cellular Phones). Experimental results and comparisons provide the effectiveness of the proposed method.

Advanced SVG triangulation/polygonalization of digital images

The paper presents two techniques to convert raster images in a Scalable Vector Graphics format. The first method is a technique that generates a Data Dependent Triangulation just by swapping the edges generated by a regular triangulation; the second technique is a Wavelet Based Triangulation and generates a multi-level triangulation based on the data collected from the wavelet multi-level transformation. After triangulation step a further reduction is introduced by a suitable polygonalization step. The proposed techniques have been compared with other raster to vector conversions in terms of both perceptual and measured quality.

A Novel Artificial Mosaic Generation Technique Driven by Local Gradient Analysis

Art often provides valuable hints for technological innovations especially in the field of Image Processing and Computer Graphics. In this paper we present a novel method to generate an artificial mosaic starting from a raster input image. This approach, based on Gradient Vector Flow computation and some smart heuristics, permit us to follow the most important edges maintaining at the same time high frequency details. Several examples and comparisons with other recent mosaic generation approaches show the effectiveness of our technique.

Adaptive techniques for microarray image analysis with related quality assessment

We propose novel techniques for microarray image analysis. In particular, we describe an overall pipeline able to solve the most common problems of microarray image analysis. We pro- pose the microarray image rotation algorithm (MIRA) and the statis- tical gridding pipeline (SGRIP) as two advanced modules devoted to restoring the original microarray grid orientation and to detecting, the correct geometrical information about each spot of input mi- croarray, respectively. Both solutions work by making use of statis- tical observations, obtaining adaptive and reliable information about each spot property. They improve the performance of the microarray image segmentation pipeline (MISP) we recently developed. MIRA, MISP, and SGRIP modules have been developed as plug-ins for an advanced framework for microarray image analysis. A new quality measure able to effectively evaluate the adaptive segmentation with respect to the fixed (e.g., nonadaptive) circle segmentation of each spot is proposed. Experiments confirm the effectiveness of the pro- posed techniques in terms of visual and numerical data.