Relating Statistical Image Differences and Degradation Features
نویسندگان
چکیده
Document images are degraded through bilevel processes such as scanning, printing, and photocopying. The resulting image degradations can be categorized based either on observable degradation features or on degradation model parameters. The degradation features can be related mathematically to model parameters. In this paper we statistically compare pairs of populations of degraded character images created with different model parameters. The changes in the probability that the characters are from different populations when the model parameters vary correlate with the relationship between observable degradation features and the model parameters. The paper also shows which features have the largest impact on the image.
منابع مشابه
An Automated MR Image Segmentation System Using Multi-layer Perceptron Neural Network
Background: Brain tissue segmentation for delineation of 3D anatomical structures from magnetic resonance (MR) images can be used for neuro-degenerative disorders, characterizing morphological differences between subjects based on volumetric analysis of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF), but only if the obtained segmentation results are correct. Due to image arti...
متن کاملImage Stitching of the Computed Radiology images Using a Pixel-Based Approach
In this paper, a method for automatic stitching of radiology images based on pixel features has been presented. In this method, according to the smooth texture of radiological images and in order to increase the number of the extracted features after quality enhancement of initial radiology images, 45 degree isotropic mask is applied to each radiology image to observe the image details. After t...
متن کاملMeasurement of the correlation coefficients between extracted features from CT and MR images
Introduction: Nowadays applying computer in image processing is being improved revolutionary for solving medical images deficiencies. Image features that are analysis in image processing show image information. The aim of the present study was to find correlation between CT- scan and MRI images' features. Materials and Methods: After data acquisition, applying...
متن کاملAn extended feature set for blind image steganalysis in contourlet domain
The aim of image steganalysis is to detect the presence of hidden messages in stego images. We propose a blind image steganalysis method in Contourlet domain and then show that the embedding process changes statistics of Contourlet coefficients. The suspicious image is transformed into Contourlet space, and then the statistics of Contourlet subbands coefficients are extracted as features. We us...
متن کاملImage authentication using LBP-based perceptual image hashing
Feature extraction is a main step in all perceptual image hashing schemes in which robust features will led to better results in perceptual robustness. Simplicity, discriminative power, computational efficiency and robustness to illumination changes are counted as distinguished properties of Local Binary Pattern features. In this paper, we investigate the use of local binary patterns for percep...
متن کامل