Digitization of many documents in public institutions is performed with the use of optical scanner with fixed scanned area size. Therefore, scanned document does not always fill all the image area and may contain additional marginal noise. A major difficulty is the appearance of borders area, which can have varying pixel intensity with additional distortions. In this paper, a novel algorithm for fast detection of the document area in scanned images is proposed. It consists of three main stages: preprocessing, edge density projections and black run analysis. The experimental results on several scanned images with different size of document have demonstrate the 86.1% accuracy document content with fast processing speed.
The procedure of camera color calibration ensures accurate and repeatable acquisition of scene colors. The main process of calibration procedure is the color transformation from camera RGB color space to device independent color space, such as CIEXYZ or CIELAB. Typical calibration procedure assumes the uniformity of irradiance across the whole scene, but such assumption is difficult to achieve. Spatial changes in irradiance are typical for indoor and outdoor light conditions. The problem of color calibration under non-uniform lighting was researched by, e.g., B. Funt and P. Bastani. In the present article, their calibration procedure was tested together with the classic approach to camera calibration. Based on these experiments a modification was proposed, in which RGB image values are scaled accordingly to the results of additional measurements. This modification allows to obtain, in conditions of spatially nonuniform scene illumination, lower values of color differences ΔE * ab and ΔE00 than in cases of classic method and FuntBastani method.
KEYWORDS: Vignetting, Cameras, Systems modeling, Data modeling, Visual process modeling, Imaging systems, Image visualization, Machine vision, Image quality, Lab on a chip
The vignetting refers to the fall-off of pixel intensity from the center towards the edges of the image. The correction of vignetting is a required pre-processing step in many applications of machine vision. In this paper, we propose a new local polynomial model of vignetting. The order of the polynomial is a parameter of the model and allows to fit the model to the real vignetting of the camera-lens system. The novelty of the proposed model is a usage of local fitting of the model to vignetting data, in contrast to the global models described in the literature. The new model was tested on two camera-lens systems with radial and non-radial vignetting, and has been compared with methods known from the literature. Based on the obtained results the proposed model gives the best quality of vignetting correction among the tested models of vignetting.
The procedure of colorimetric calibration of the camera ensures accurate and repeatable acquisition of the scene colors. The most common approach defines the calibration only as the color transformation between the camera image colors and colorimetric colors. The only condition for image acquisition is an uniform illumination of the scene. Unfortunately, such assumption does not include many distortions caused by image acquisition. One of them is a vignetting, which can be described as a decrease of the light intensity from the image center to the image corners. This phenomenon causes the same effects as non-uniform illumination, which is the change of color values of the same object depending on image coordinates. This paper is an attempt to analyze the influence of vignetting correction on the results of the camera colorimetric calibration. The conducted experiment in uniform light conditions shows that the improvement of calibration quality depends on the chosen vignetting correction method.
The quality of image often decides about its usability in further application. Hence, it is essential to ensure the best possible image quality at the stage of the image acquisition process. The lighting conditions are one of the most important factors affecting the quality of the obtained image. In the case of hyperspectral imaging, in comparison to standard image acquisition, selection of appropriate light sources involves additional difficulties connected with the spectral nature of the light. The article describes how the lights for such application can be selected. The proposed selection criterion is based on the accuracy of measured spectral reflectance of the object. Presented method was tested on real object and three different types of light source.
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