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In this paper we present an approach for fruit recognition using artificial vision, towards to employ it as an application for supermarkets. The fruit's visual features extracted are shape, texture and ‑we focus on‑ the extraction of the color chromaticity. From the few related works on fruit recognition, the color extraction is performed in the RGB (Red, Green, Blue) space. We claim as necessary...
Digital ink texts in Chinese can neither be converted into users' desired layouts nor be recognized until their characters, lines, and paragraphs are correctly extracted. There are many errors in automatically segmented digital ink texts in Chinese because they are free forms and mixed with other languages, as well as their Chinese characters have small gaps and complex structures. Paragraphs, lines,...
To simplify the matching and recognition of 3D objects, we propose to decompose a complex 3D shape into simpler primitive parts. Our partitioning of objects relies on their topological Reeb graphs. Taking advantage of the properties of Morse theory, we detect the critical points of the global geodesic function. These points define the levels at which the segmentation happens. To preserve the geometry...
In this paper we propose a novel computational method to infer visual saliency in images. The method is based on the idea that salient objects should have local characteristics that are different than the rest of the scene, being edges, color or shape. By using a novel operator, these characteristics are combined to infer global information. The obtained information is used as a weighting for the...
Our goal is to organize the image contents semantically. In this paper, we propose a method to classify the images semantically, using the C-fuzzy algorithm to segment the natural scenes into perceptually uniform regions. The low-level characteristics that are taken into account are: color, texture, shape, absolute spatial arrangement, spatial coherency, and dimension. Since humans are the ultimate...
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