Adopting Biological Sequence Alignment Tools in 2D Shape Recognition
نویسندگان
چکیده
منابع مشابه
A fuzzy approach to 2D-shape recognition
This paper describes a method for fuzzy classification and recognition of two-dimensional (2-D) shapes, such as handwritten characters, image contours, etc. A fuzzy model is derived for each considered shape from a fuzzy description of a set of instances of this shape. A fuzzy description of a shape instance, in its turn, exploits appropriate fuzzy partitions of the two dimensions of the shape....
متن کامل2D Shape Recognition by Hidden Markov Models
In Computer Vision, two-dimensional shape classifcation is a complex and well studied topic, often basic for three-dimensional object recognition. Object contours are a widely chosen feature for representing objects, useful in many respects for classifcation problems. In this paper; we address the use of Hidden Markov Models (HMMs) for shape analysis, based on chain code representation of objec...
متن کاملAlignment-Based Recognition of Shape Outlines
We present a 2D shape recognition and classification method based on matching shape outlines. The correspondence between outlines (curves) is based on a notion of an alignment curve and on a measure of similarity between the intrinsic properties of the curve, namely, length and curvature, and is found by an efficient dynamic-programming method. The correspondence is used to find a similarity me...
متن کاملBiological Sequence Alignment on Graphics Processing Units
Sequence alignment is a common and often repeated task in molecular biology. The need for speeding up this treatment comes from the rapid growth rate of biological sequence databases. In this paper we present a new approach to high performance biological sequence database scanning on graphics processing units. Using modern graphics processing units for high performance computing is facilitated ...
متن کاملBiological Database Normalization by Sequence Alignment
The Michigan Molecular Interactions (MiMI) database contains protein interaction data from many distinct sources. Frequently, the same protein is referred to in different external databases by different identifiers, so it is difficult to determine when different records refer to the same object. The normalization problem is addressed by creating an extended MiMI database that integrates MiMI wi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Innovative Research in Science, Engineering and Technology
سال: 2015
ISSN: 2347-6710,2319-8753
DOI: 10.15680/ijirset.2015.0408036