Thinning algorithim on 2D gray-level images
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Thinning on binary images is widely discussed in the past three decades. A binary image can be obtained by thresholding a gray-level image. For preventing possible information losses in the thresholding process, it may be natural to design thinning algorithms directly on the original gray-level images. This paper proposes a two-step template-based thinning algorithm on gray-level images. The first step of the algorithm is to extract 4-connected gray-level skeletons from gray-level objects. The second step is to extract 8-connected gray-level skeletons from the consequent result of the first step.Keywords:
Gray (unit)
Gray level
Thinning
Balanced histogram thresholding
Multiscale representation of images is extremely often applied in various fields, and as proven before, the centroid-based algorithm for binary images is effective. In this paper, a new centroid-based algorithm of multiscale representation for greyscale images is presented. The same with binary images, the approach is able to preserve symmetry of the original image and even keep its shape or topology. Also in this paper, a greyscale image is supposed as a 3-D binary image in order to apply multiscale representation for binary image. All examples in this paper show that the new method can be efficiently applied in many different fields.
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Representation
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Aiming at the problems existing in the image texture detection,it is put forward a new method of Parallel Gray Level Grade Co-Occurrence Matrix.At first it is needed to determine the image grayscale distribution and to obtain the difference of information as separate categories;then through gray level-gradient co-occurrence matrix,it is calculated the change rate of the image grayscale.At last the channel process is decided and the pixel interconnected mapping test is made.Multichannel parallel process is the multiplication of single channel probability data of interconnection events.Experimental result shows this texture detection method is effective.
Co-occurrence matrix
Gray level
Texture (cosmology)
Matrix (chemical analysis)
Gray (unit)
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Gray level co-occurrence matrix (GLCM) is a second-order statistical measure of image grayscale which reflects the comprehensive information of image grayscale in the direction, local neighborhood and magnitude of changes. Firstly, we analyze and reveal the generation process of gray level co-occurrence matrix from horizontal, vertical and principal and secondary diagonal directions. Secondly, we use Brodatz texture images as samples, and analyze the relationship between non-zero elements of gray level co-occurrence matrix in changes of both direction and distances of each pixels pair by. Finally, we explain its function of the analysis process of texture. This paper can provided certain referential significance in the application of using gray level co-occurrence matrix at quality evaluation of texture image.
Co-occurrence matrix
Gray level
Gray (unit)
Texture (cosmology)
Grey level
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This paper proposes a method of hiding the binary image in a grayscale image. Random numbers could be used to shuffle the binary values of an image. Invert is an operation that complements 0s and 1s of binary image. Pixel matching is a technique that could be used to is also used to extract the binary bits and compare the stego-image with original image. This work aims to generate random numbers with less detectability as well as higher embedding capacity through inverting the binary image. Experiments are made among open source grayscale images and the results with higher Peak Signal Noise Ratio (PSNR) and good visual quality in images obtained.
Peak signal-to-noise ratio
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Balanced histogram thresholding
Speedup
Image histogram
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Mathematical morphology provides an efficient tool for image analysis. We study the problem of flaw detection in materials which are represented by very poor contrast digital images. An algorithm for flaw detection in the case of glass matte surfaces has been developed. The object skeletons within the binary images are obtained and directional connectivity information in the skeletons is used to discriminate noise patterns from flaws according to a specified criteria. After the discrimination process, the remaining skeletons correspond to flaws and can be employed to recover the shape of flaws. An alarm flag may be turned on if the sizes of the detected flaws are found to exceed industrial standards. In the case of a grayscale image, the image is converted to a binary version by using an adaptive threshold algorithm, then the algorithm for binary images is applied. Experimental results have been obtained for both binary and grayscale digital image data.
Machine Vision
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Thresholding converts a greyscale image into a binary image, and is thus often a necessary segmentation step in image processing. For a human viewer however, thresholding usually has a negative impact on the legibility of document images. This report describes a simple method for "smearing out" the threshold and transforming the greyscale image into a different greyscale image. The method is similar to fuzzy thresholding, but is discussed here in the simpler context of greyscale transformations and, unlike fuzzy thresholding, it is independent from the method for finding the threshold. A simple formula is presented for automatically determining the width of the threshold spread. The method can be used, e.g., for enhancing images for the presentation in online facsimile repositories.
Balanced histogram thresholding
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Liquid crystal display regarded as a type of display is desired to have its electrocircuit as simple as possible and its power consumption low,and to be integrated;also as a picture displayer,it is hoped to have adequate gray grade and stable with no glinting.More gray grade could make picture layer more clear and picture more subdued,so it is important to have gray grade expression of display.This article analyzes the grayscale algorithm and control circuit already employed for single-color dot matrix liquid crystal display based on FPGA at home and abroad,especially studies phase distribution law.A new formula algorithm was developed on basis of that it uses real time picture data processing to remove the disadvantage of large area and high power consumption,at the same time the algorithm is analyzed carefully and detailedly.
Gray level
Gray (unit)
High color
Matrix (chemical analysis)
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