Local object gist: meaningful shapes and spatial layout at a very early stage of visual processing

In his introduction, Pinna (2010) quoted one of Wertheimer’s observations: “I stand at the window and see a house, trees, sky. Theoretically I might say there were 327 brightnesses and nuances of color. Do I have ‘327’? No. I have sky, house, and trees.” This seems quite remarkable, for Max Wertheimer, together with Kurt Koffka and Wolfgang Koehler, was a pioneer of Gestalt Theory: perceptual organisation was tackled considering grouping rules of line and edge elements in relation to figure-ground segregation, i.e., a meaningful object (the figure) as perceived against a complex background (the ground). At the lowest level – line and edge elements – Wertheimer (1923) himself formulated grouping principles on the basis of proximity, good continuation, convexity, symmetry and, often forgotten, past experience of the observer. Rubin (1921) formulated rules for figure-ground segregation using surroundedness, size and orientation, but also convexity and symmetry. Almost a century of research into Gestalt later, Pinna and Reeves (2006) introduced the notion of figurality, meant to represent the integrated set of properties of visual objects, from the principles of grouping and figure-ground to the colour and volume of objects with shading. Pinna, in 2010, went one important step further and studied perceptual meaning, i.e., the interpretation of complex figures on the basis of past experience of the observer. Re-establishing a link to Wertheimer’s rule about past experience, he formulated five propositions, three definitions and seven properties on the basis of observations made on graphically manipulated patterns. For example, he introduced the illusion of meaning by comics-like elements suggesting wind, therefore inducing a learned interpretation. His last figure shows a regular array of squares but with irregular positions on the right side. This pile of (ir)regular squares can be interpreted as the result of an earthquake which destroyed part of an apartment block. This is much more intuitive, direct and economic than describing the complexity of the array of squares.

Automatic processing of bidimensional images of ''omic'' expression blobs

In this work, a comprehensive review on automatic analysis of Proteomics and Genomics images is presented. Special emphasis is given to a particularly complex image produced by a technique called Two-Dimensional Gel Electrophoresis (2-DE), with thousands of spots (or blobs). Automatic methods for the detection, segmentation and matching of blob like features are discussed and proposed. In particular, a very robust procedure was achieved for processing 2-DE images, consisting mainly of two steps: a) A very trustworthy new approach for the automatic detection and segmentation of spots, based on the Watershed Transform, without any foreknowledge of spot shape or size, and without user intervention; b) A new method for spot matching, based on image registration, that performs well for either global or local distortions. The results of the proposed methods are compared to state-of-the-art academic and commercial products.