1,721,045 research outputs found
On the computational complexity of multivariate median filters
No full textThough the noise removal capability of multivariatemedianfilters has been carefully investigated, a comprehensive analysis of their complexity is still missing. In this work, the complexity of the most commonly used multivariatemedianfilters is thoroughly analyzed. For each filter theoretical results are derived and validated against experimental data, proving that computationalcomplexity depends mainly on the approach adopted to sort multivariate samples. Algorithms based on marginal ordering are very fast, whereas the use of an ordering scheme based on the aggregate sum of distances leads to very slow algorithms. An intermediate behavior is observed for filters relying on reduced ordering. A fast algorithm for the implementation of the vector median based on 1-norm is also described which significantly reduces the complexity of this filter
Art-work image processing and transmission
No full textAfter a brief presentation of the scenario of Italian activities in national and EU projects, concerning processing and transmission of Art-Works images, some researches aimed at color correction carried out at the Uffizi Gallery Labs are described, and applications of remote processing for color certification are outlined. Interactions with the national project "Knowledge Through Images: an Application to Cultural Heritage" are highlighted as well
A coarse-to-fine algorithm for fast median filtering of image data with a huge number of levels
No full textA two-step algorithm exploiting a reduced local grey-level histogram is proposed for efficient running-median calculation in digital monochrome images whose number of levels is considerably large, such as medical images, SAR images, or 2-D data maps. The first step borrows the concept of sliding window for fast update of the local histogram, as well as the strategy of percentile upgrade for fast median retrieval, and provides a coarse estimate of the actual median which is refined in the second stage, involving only a limited portion of the histogram. Comparisons in terms of theoretical number of operations evidence a computing time O(L2) instead of O(L), where L = L1.L2 is the number of levels, and L1 is the size of the reduced histogram. Also computer tests validate the ideal relationship and suggest a practical factorization criterion of the local histogram, when dealing with natural correlated images. Experimental results substantially prove the validity of the novel algorithm as a feasible alternative, for calculation of any rank-order value, to level-sorting techniques, whenever both classic histogram-based schemes and sorting algorithms are prohibitively time-consuming, as it happens in some practical image processing applications
Colour-based detection of defects on chicken meat
No full textExisting vision-based automatic inspection systems are mainly devoted to mechanic and electronic applications, their introduction into other fields being strongly limited by the need for operating in non-controlled environments and by the lack of an accurate definition of the inspection task. In this paper, an intelligent vision system aimed at the detection of defects on chickenmeat before packing is presented. The detection of defects relies on the analysis of the chromatic content of chicken images. Possibly defective areas are first extracted by means of morphological image reconstruction, and then classified according to a predefined list of defects. Experimental results show the effectiveness of the proposed approach, thus proving the feasibility of automatic inspection of alimentary products
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