The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Recognition of humans based on characteristic eye features has taken a significant place in security and identification systems in the past two decades. The complex pattern of the iris, that is unique to an eye, makes iris a great biometric descriptor. The first step in the process of the biometric identification based on iris is its localization in an image. The shape of the iris, its size, position,...
In this study, a method of thresholding is proposed that based on the histogram shape of each image, proposes the more appropriate technique from the famous and common thresholding techniques. Thresholding, which is a commonly used operation for image processing, is the selection of one of the image pixels that determines the border for background and foreground of the image. After determining a suitable...
Oil spill detection becomes very important nowadays, due to the importance of oil and to prevent pollution caused by oil leakage. Synthetic Aperture Radar (SAR) images show oil spill boundaries clearly. An oil spill appears as an obscure spot in SAR images. Therefore, thresholding is considered the best method to extract this patch and define its boundaries clearly. This paper proposes a novel thresholding...
The purpose of our work is to define an original approach to determine the threshold of unimodal image histograms in a robust manner. Our proposed segmentation approach refers to Shannon entropy. Threshold estimation is based on the exploitation of the curve of the entropy loss quantity. The final expression of the sigmoid estimated function of the entropy error and derivatives are used to select...
We explore problem of ship target segmentation in infrared (IR) images, and propose an efficient method. The method consists of two procedures: first, based on the intensity properties of target and background region, we design a global background subtraction filter (GBSF) to suppress the background, and an adaptive row mean subtraction filter (ARMSF) to enhance the target. By iteratively applying...
Attribute filters allow enhancement and extraction of features without distorting their borders, and never introduce new image features. These are highly desirable properties in biomedical imaging, where accurate shape analysis is paramount. However, setting the attribute-threshold parameters has to date only been done manually. This paper explores simple, fast and automated methods of computing attribute...
Image Segmentation is one of important tasks in conventional or document image processing. Tsallis-entropy based image thresholding method has been considered one of the most efficient ways for image segmentation. At present one useful way in entropy-thresholding segmentation is based 2D vertical segmentation, but obvious limitations exist in this approach. In this paper, a method 2D obique segmentation...
Image thresholding method based on generalized fuzzy entropy segments the image using the principle that the membership degree of the threshold point is equal to m (0<m<1), better segmentation result can be obtained than that of traditional fuzzy entropy method, especially for images with bad illumination. The main problem of this method is how to determine the parameter m effectively. In this...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.