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Edge of image is one of the most fundamental and significant features. Edge detection is always one of the classical studying projects of computer vision and image processing field. It is the first step of image analysis and understanding. With the continuous improvement of remote sensing image, especially the appearance of Digital Aerial Image, edge detection is necessary step to extract information...
Handwritten character recognition has received extensive attention in academic and production fields. The recognition system can be either on-line or off-line. Off-line handwriting recognition is the subfield of Optical Character Recognition . In this paper, We introduce the fundamental principles of Chinese handwritten numerals, including digital image preprocessing, segmentation, features extraction...
Character recognition has been in importance for several decades. Lot of research interest are now focused on applying pattern recognition and computer vision algorithms on camera captured documents to retrieve information from the documents. This paper presents a novel approach for extracting text in camera captured images using edge based algorithm. Extensive experiments have been carried out on...
In this paper a nonparametric contextual classification using both spectral and spatial information will be proposed for hyperspectral image classification. Essentially, among the classification, spatial information is acquired on the basis of Markov random field (MRF) and then joined with the nonparametric density estimation. Two MRF-based nonparametric contextual classifications based on kNN and...
In allusion to the present heterotrophic bacteria colony counting method having the disadvantages of subjectivity, big error and low efficiency, we proposed a recognition method for heterotrophic bacteria colony based on SVM. After a series of pre-processing and segmentation to the acquired colony image, 6 feature parameters such as: area, perimeter, equivalent diameters of colony individual and non-colony...
Usage of statistical classifiers, namely AdaBoost and its modifications, in object detection and pattern recognition is a contemporary and popular trend. The computatiponal performance of these classifiers largely depends on low level image features they are using: both from the point of view of the amount of information the feature provides and the executional time of its evaluation. Local rank difference...
This correspondence first kernalizes the region covariance matrix and formalizes the similarity metric using four block matrices. The effectiveness of the proposed methods is proven with experiments on face recognition.
Automatic classification of chromosome images used in karyotyping has been of interest for many years. Regardless of the efforts put into this field, due to the complexity of the matter, still the functional accuracy of current automated systems is much lower than a human operator. Since the interdiction of SVM and its proven efficacy in pattern recognition both in theory and application, we decided...
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