• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 51
  • 4
  • 2
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • Tagged with
  • 58
  • 58
  • 24
  • 15
  • 14
  • 9
  • 9
  • 9
  • 7
  • 5
  • 5
  • 4
  • 3
  • 3
  • 3
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

An investigation of a mathematical model to characterize the nonlinear nature of a lithographic film system /

Holbrook, David S. January 1981 (has links)
Thesis (M.S.)--Rochester Institute of Technology, 1981. / Typescript. Includes bibliographical references (leaf 50).
2

Increased image resolution and film efficiency via vacuum platens and other mechanical devices /

Ruffing, James A. January 1980 (has links)
Senior research project (B.S.)--Rochester Institute of Technology. / Typescript.
3

Mathematical modeling of black-and-white chromogenic image stability /

Datema, Charles Philip. January 1982 (has links)
Thesis (M.S.)--Rochester Institute of Technology, 1982. / Typescript. Includes bibliographical references (leaves 56-58).
4

On the statistics of natural images /

Chen, Ting-Li. January 2005 (has links)
Thesis (Ph.D.)--Brown University, 2005. / Vita. Thesis advisor: Stuart Geman. Includes bibliographical references (leaves 87). Also available online.
5

Solving for relative orientation and depth

McReynolds, Daniel Peter January 1988 (has links)
A translating and rotating camera acquires images of a static scene from disparate viewpoints. Given a minimum number of corresponding image tokens from two or more images, the rotation and translation (referred to as the relative orientation) of the camera, and the relative depths of the tokens, can be computed between the views. Image tokens, which can be points or lines, are deemed corresponding if they arise from the same physical entity. The process of determining corresponding tokens is assumed to be known. This thesis poses the problem of solving for relative orientation and depth. The solution to this problem has applications in building object or scene models from multiple views and in passive navigation. A minimum of five corresponding pairs of points, measured from two perspective projection images, are required. In the case of lines, the measurements of six corresponding sets of lines, from a minimum of three images, are necessary for a unique solution. The algorithm simultaneously determines the rotation and translation of the camera between the images and the three dimensional position of the matched scene tokens. The translation and depth can only be determined up to a global scale factor. It is assumed that the motion of the camera or object is rigid. The equations that describe the motion and scene structure are nonlinear in the camera model parameters. Newton's method is used to perform the nonlinear parameter estimation. The camera model is based on the collinearity condition, well known in the area of photogrammetry. This condition states that the focal point, image point and object point must all lie on the same line under perspective projection. This approach differs from other similar approaches in the choice of model parameters and in the formulation of the collinearity condition. The formulation for line correspondences turns out to be an easy extension of the point formulation. To improve the range of convergence and the robustness of the algorithm, the Levenberg-Marquardt extension for discrete least squares is applied to the over-determined system. Results from a Monte Carlo simulation with noise-free images indicate a range of convergence for rotation of approximately plus or minus sixty degrees. Simulations with noisy images (image measurements perturbed by plus or minus three pixels) yield a range of convergence for rotation of approximately plus or minus forty degrees. The range of convergence in translation is in the order of twice the length of the translation vector in any direction parallel to the image plane. For translation orthogonal to the image plane, the range of convergence is approximately eighty percent of the length of the translation vector. Simulations with the same noisy images generated for the rotation tests, indicate that the range of convergence for translation is not appreciably affected by these noise levels. Tests with real images, in which a 3D model of an object is derived from multiple views with human assistance in determining line correspondences, yield results that agree reasonably well with the noisy image simulations. / Science, Faculty of / Computer Science, Department of / Graduate
6

The effect of environment on latent image formation and stability /

O'Toole, Sean W. P. January 1995 (has links)
Thesis (M.S.)--Rochester Institute of Technology, 1995. / Typescript. Includes bibliographical references (leaves 37-40).
7

Report on the fast boundary detection algorithm of Werner Frei and Chung-Ching Chen

Schowengerdt, Daniel Benjamin January 2010 (has links)
Typescript (photocopy). / Digitized by Kansas Correctional Industries
8

Influence of first developer solvent levels on the information storage capacity of negative and reversal images /

Harrison, Wendy R. January 1980 (has links)
Thesis (M.S.)--Rochester Institute of Technology. / Typescript. Includes bibliographical references.
9

Design and production of a comprehensive graininess scale for use in electrophotography /

Mueller, Susan B. January 1980 (has links)
Thesis (M.S.)--Rochester Institute of Technology. / Typescript. Includes bibliographical references.
10

Digital image modeling of film granularity and effect of subjective pictorial quality /

Lisson, Jerold B. January 1981 (has links)
Thesis (M.S.)--Rochester Institute of Technology, 1981. / Typescript. Includes bibliographical references (leaf 73).

Page generated in 0.0655 seconds