The Standard Hough Transform (SHT) is used to find lines, circles and other image features in edge maps containing edge points. Edge points which potentially can ‘vote’ for a given line (called its ‘line support’) are highly dependent of line position and orientation due to the boundedness of images. If accumulator array peaks are used to find lines then peripherally located lines are missed. U...

Laplace's tidal equation for diurnal tides of longitudinal number one is investigated. It is found that in addition to the previously found solutions (Hough Functions) corresponding to positive equivalent depths there are also Hough Functions corresponding to negative equivalent depths. Both are necessary for the representation of observed tidal data. As an application of the Hough Functions th...

رابطه‌­ی شدت ترمولومینسانس براساس مدل سینتیک مرتبه‌­ی اول بدون در نظرگرفتن اثر فروکشی دمایی مورد استفاده قرار می‌­گیرد. این حالی است که به عنوان یک واقعیت فیزیکی باید روابط بیان‌­کننده‌­ی توجه گیرد. کار با نظر گرفتن برای اول، تابع جداسازی منحنی تابش جدیدی برحسب و دمای قله دست آمد. نحوی جدید حذف مشخصه‌­های دمایی، همان قبلی خود تبدیل می‌­شود. دزیمتر (400TLD-) :Mn2CaF بررسی گرفت. این‌­که ­شدت طبق ...

Recent advances in microscopy enable the capture of temporal sequences during cell development stages. However, the study of such sequences is a complex and time consuming task. In this paper we propose an automatic strategy to address the problem of semantic and instance segmentation of mouse embryos using NYU’s Mouse Embryo Tracking Database. We obtain our instance proposals as refined predic...

This paper discusses the Randomized Hough Transform used to find ellipses in images. The equations to find ellipses and their implementation in the algorithm are explained. The algorithm performed well, finding ellipses of orientation 0o and 9Oo from the x-axis in various images. Ellipses were also found in a real-world image after preprocessing.

In this paper, we present a new method for twodimensional (2D) shape detection applicable under affine transformation. The problem of affine-invariant shape detection is an important and fundamental research subject in computer vision. Although various methods have been proposed to solve this problem, most of those approaches are not well suited for the following general cases: (1) a shape to b...

This paper proposes a new method for recognition of geometrical shapes (such as lines, circles or ellipsoids) in an image. The main idea is to transform the problem into a bounded error estimation problem and then to use an interval-based method which is robust with respect to outliers. The approach is illustrated on an image taken by an underwater robot where a spheric buoy has to be detected....

This paper describes the detection of faces in complex backgrounds where their sizes, positions and directions are arbitrary. We detect the faces by extracting face components such as eyes, a mouth and so on. We first extract face features and then calculate their likelihoods as each face component. Second we detect the face features which satisfy geometrical relations of the face. In order to ...

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