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Proper recognition of microscopic sperm cells in video images is an important step in diagnosis and treatment of male infertility. The small sizes of the sperm cells make their segmentation and detection an important stage in the microscopic images analysis. Histogram-based thresholding schemes are one of the common approaches for this purpose. This paper proposes a non-linear amplitude compression...
Entropy-based image thresholding has received considerable interest in recent years. It is an important concept in the area of image segmentation. The entropy-based approach was used to get the threshold of image from 80 ages; it is used to weight the amount of reserved information of image after segmentation. Our contribution in this paper, is to explain the idea of Shannon entropy and how he utilized...
In image clustering, digital images can be represented with a large number of visual features corresponding to a high dimensional data space. Traditional clustering algorithms have difficulty in processing image dataset because of the curse of dimensionality. Moreover, similarity between images is measured by the values of partial features. To discover clusters existing in different subspace is known...
In this work we explore the task of authenticating and dating ancient manuscripts by capturing images of pages in near infrared (NIR) and modelling and then comparing the ink appearance of segmented text. We present a texture feature descriptor to characterize and recognize semi-transparent materials such as the inks found in manuscripts. These textural patterns are different in nature from perceptual...
Image segmentation is a major step in image analysis and processing. Segmentation is performed through several methods. In this work Niblack's method of segmentation is further studied. It is one of the local thresholding techniques for segmentation. The output of Niblack's method is significant and has most acceptable result out of all thresholding techniques in segmenting text documents. In this...
Thresholding is an important operation in image analysis which is used in many applications. One of the most efficient techniques for image segmentation is the entropy-based thresholding technique. A popular entropy-based thresholding method is the Kapur thresholding method. In this method, the criterion to select a suitable threshold is the maximization of the Kapur's entropies based on gray-level...
Image segmentation plays an important role in image analysis and computer vision system. Among all segmentation techniques, the automatic thresholding methods are widely used because of their advantages of simple implement and time saving. Otsu method is one of thresholding methods and frequently used in various fields. Two-dimensional (2D) Otsu method behaves well in segmenting images of low signal-to-noise...
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