4,444 research outputs found
Automatic Image Registration in Infrared-Visible Videos using Polygon Vertices
In this paper, an automatic method is proposed to perform image registration
in visible and infrared pair of video sequences for multiple targets. In
multimodal image analysis like image fusion systems, color and IR sensors are
placed close to each other and capture a same scene simultaneously, but the
videos are not properly aligned by default because of different fields of view,
image capturing information, working principle and other camera specifications.
Because the scenes are usually not planar, alignment needs to be performed
continuously by extracting relevant common information. In this paper, we
approximate the shape of the targets by polygons and use affine transformation
for aligning the two video sequences. After background subtraction, keypoints
on the contour of the foreground blobs are detected using DCE (Discrete Curve
Evolution)technique. These keypoints are then described by the local shape at
each point of the obtained polygon. The keypoints are matched based on the
convexity of polygon's vertices and Euclidean distance between them. Only good
matches for each local shape polygon in a frame, are kept. To achieve a global
affine transformation that maximises the overlapping of infrared and visible
foreground pixels, the matched keypoints of each local shape polygon are stored
temporally in a buffer for a few number of frames. The matrix is evaluated at
each frame using the temporal buffer and the best matrix is selected, based on
an overlapping ratio criterion. Our experimental results demonstrate that this
method can provide highly accurate registered images and that we outperform a
previous related method
Approximating the Maximum Overlap of Polygons under Translation
Let and be two simple polygons in the plane of total complexity ,
each of which can be decomposed into at most convex parts. We present an
-approximation algorithm, for finding the translation of ,
which maximizes its area of overlap with . Our algorithm runs in
time, where is a constant that depends only on and .
This suggest that for polygons that are "close" to being convex, the problem
can be solved (approximately), in near linear time
matching, interpolation, and approximation ; a survey
In this survey we consider geometric techniques which have been used to
measure the similarity or distance between shapes, as well as to approximate
shapes, or interpolate between shapes. Shape is a modality which plays a key
role in many disciplines, ranging from computer vision to molecular biology.
We focus on algorithmic techniques based on computational geometry that have
been developed for shape matching, simplification, and morphing
Image Processing Applications in Real Life: 2D Fragmented Image and Document Reassembly and Frequency Division Multiplexed Imaging
In this era of modern technology, image processing is one the most studied disciplines of signal processing and its applications can be found in every aspect of our daily life. In this work three main applications for image processing has been studied.
In chapter 1, frequency division multiplexed imaging (FDMI), a novel idea in the field of computational photography, has been introduced. Using FDMI, multiple images are captured simultaneously in a single shot and can later be extracted from the multiplexed image. This is achieved by spatially modulating the images so that they are placed at different locations in the Fourier domain. Finally, a Texas Instruments digital micromirror device (DMD) based implementation of FDMI is presented and results are shown.
Chapter 2 discusses the problem of image reassembly which is to restore an image back to its original form from its pieces after it has been fragmented due to different destructive reasons. We propose an efficient algorithm for 2D image fragment reassembly problem based on solving a variation of Longest Common Subsequence (LCS) problem. Our processing pipeline has three steps. First, the boundary of each fragment is extracted automatically; second, a novel boundary matching is performed by solving LCS to identify the best possible adjacency relationship among image fragment pairs; finally, a multi-piece global alignment is used to filter out incorrect pairwise matches and compose the final image. We perform experiments on complicated image fragment datasets and compare our results with existing methods to show the improved efficiency and robustness of our method.
The problem of reassembling a hand-torn or machine-shredded document back to its original form is another useful version of the image reassembly problem. Reassembling a shredded document is different from reassembling an ordinary image because the geometric shape of fragments do not carry a lot of valuable information if the document has been machine-shredded rather than hand-torn. On the other hand, matching words and context can be used as an additional tool to help improve the task of reassembly. In the final chapter, document reassembly problem has been addressed through solving a graph optimization problem
Shape matching by curve modelling and alignment
Automatic information retrieval in the eld of shape recognition has been widely covered by many
research elds. Various techniques have been developed using different approaches such as intensity-based, modelbased
and shape-based methods. Whichever is the way to represent the objects in images, a recognition method
should be robust in the presence of scale change, translation and rotation. In this paper we present a new recognition
method based on a curve alignment technique, for planar image contours. The method consists of various phases
including extracting outlines of images, detecting signicant points and aligning curves. The dominant points can
be manually or automatically detected. The matching phase uses the idea of calculating the overlapping indices
between shapes as similarity measures. To evaluate the effectiveness of the algorithm, two databases of 216 and
99 images have been used. A performance analysis and comparison is provided by precision-recall curves
3-D facial expression representation using B-spline statistical shape model
Effective representation and recognition of human faces are essential in a number of applications including human-computer interaction (HCI), bio-metrics or video conferencing. This paper presents initial results obtained for a novel method of 3-D facial expressions representation based on the shape space vector of the statistical shape model. The statistical shape model is constructed based on the control points of the B-spline surfaces of the train-ing data set. The model fitting for the data is achieved by a modified iterative closest point (ICP) method with the surface deformations restricted to the es-timated shape space. The proposed method is fully automated and tested on the synthetic 3-D facial data with various facial expressions. Experimental results show that the proposed 3-D facial expression representation can be potentially used for practical applications
Digital representation of historical globes : methods to make 3D and pseudo-3D models of sixteenth century Mercator globes
In this paper, the construction of digital representations of a terrestrial and celestial globe will be discussed. Virtual digital (3D) models play an important role in recent research and publications on cultural heritage. The globes discussed in this paper were made by Gerardus Mercator (1512-1594) in 1541 and 1551. Four techniques for the digital representation are discussed and analysed, all using high-resolution photographs of the globes. These photographs were taken under studio conditions in order to get equal lighting and to avoid unwanted light spots. These lighting conditions are important, since the globes have a highly reflective varnish covering. Processing these images using structure from motion, georeferencing of separate scenes and the combination of the photographs with terrestrial laser scanning data results in true 3D representations of the globes. Besides, pseudo-3D models of these globes were generated using dynamic imaging, which is an extensively used technique for visualisations over the Internet. The four techniques and the consequent results are compared on geometric and radiometric quality, with a special focus on their usefulness for distribution and visualisation during an exhibition in honour of the five hundredth birthday of Gerardus Mercator
Locality Sensitive Hashing for Efficient Similar Polygon Retrieval
Locality Sensitive Hashing (LSH) is an effective method of indexing a set of
items to support efficient nearest neighbors queries in high-dimensional
spaces. The basic idea of LSH is that similar items should produce hash
collisions with higher probability than dissimilar items.
We study LSH for (not necessarily convex) polygons, and use it to give
efficient data structures for similar shape retrieval. Arkin et al. represent
polygons by their "turning function" - a function which follows the angle
between the polygon's tangent and the -axis while traversing the perimeter
of the polygon. They define the distance between polygons to be variations of
the (for ) distance between their turning functions. This metric
is invariant under translation, rotation and scaling (and the selection of the
initial point on the perimeter) and therefore models well the intuitive notion
of shape resemblance.
We develop and analyze LSH near neighbor data structures for several
variations of the distance for functions (for ). By applying our
schemes to the turning functions of a collection of polygons we obtain
efficient near neighbor LSH-based structures for polygons. To tune our
structures to turning functions of polygons, we prove some new properties of
these turning functions that may be of independent interest.
As part of our analysis, we address the following problem which is of
independent interest. Find the vertical translation of a function that is
closest in distance to a function . We prove tight bounds on the
approximation guarantee obtained by the translation which is equal to the
difference between the averages of and
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