A Complete Roundness Classi cation
نویسندگان
چکیده
We describe a roundness classiication procedure , that is, a procedure to determine if the roundness of a planar object I is within some 0 from an ideal circle. The procedure consists of a probing strategy and an evaluation algorithm working in a feedback loop. This approach of combining probing with evaluation is new in computational metrology. For several deenitions of roundness, our procedure uses O(1=qual(I)) probes and runs in time O(1=qual(I) 2). Here, the quality qual(I) of I measures how far the roundness of I is from the accept-reject criterion. Hence our algorithms are \quality sensitive".
منابع مشابه
Probabilistic Disease Classi cation of Expression-Dependent Proteomic Data from Mass Spectrometry of Human Serum
We have developed an algorithm called Q5 for probabilistic classi cation of healthy versus disease whole serum samples using mass spectrometry. The algorithm employs principal components analysis (PCA) followed by linear discriminant analysis (LDA) on whole spectrum surface-enhanced laser desorption/ionization time of ight (SELDI-TOF) mass spectrometry (MS) data and is demonstrated on four r...
متن کاملNavigala: an Original Symbol Classifier Based on Navigation through a Galois Lattice
This paper deals with a supervised classi ̄cation method, using Galois Lattices based on a navigation-based strategy. Coming from the ̄eld of data mining techniques, most literature on the subject using Galois lattices relies on selection-based strategies, which consists of selecting/ choosing the concepts which encode the most relevant information from the huge amount of available data. Generall...
متن کاملPartial Classification Using Association Rules
Many real-life problems require a partial classi cation of the data. We use the term \partial classi cation" to describe the discovery of models that show characteristics of the data classes, but may not cover all classes and all examples of any given class. Complete classi cation may be infeasible or undesirable when there are a very large number of class attributes, most attributes values are...
متن کاملComparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data
A reliable and precise classi cation of tumors is essential for successful diagnosis and treatment of cancer. cDNA microarrays and highdensity oligonucleotide chips are novel biotechnologies increasingly used in cancer research. By allowing the monitoring of expression levels in cells for thousands of genes simultaneously, microarray experiments may lead to a more complete understanding of the...
متن کاملImage Segmentation Through Automatic Fractal Dimension Classi ̄cation
Usual segmentation techniques of grayscale images depend on supervised trial-and-error procedures. Moreover, in noisy images, local classi ̄cation schemes fail due to the random °uctuations introduced by the noise. Recent proposals as the active contours may be robust enough to cope with some cases of noisy images without supervision (except for the initialization step), but still fail with imag...
متن کامل