Steerable filters generated with the hypercomplex dual-tree wavelet transform

The use of wavelets in the image processing domain is still in its infancy, and largely associated with image compression. With the advent of the dual-tree hypercomplex wavelet transform (DHWT) and its improved shift invariance and directional selectivity, applications in other areas of image processing are more conceivable. This paper discusses the problems and solutions in developing the DHWT and its inverse. It also offers a practical implementation of the algorithms involved. The aim of this work is to apply the DHWT in machine vision. Tentative work on a possible new way of feature extraction is presented. The paper shows that 2-D hypercomplex basis wavelets can be used to generate steerable filters which allow rotation as well as translation.</p

A machine vision extension for the Ruby programming language

Dynamically typed scripting languages have become popular in recent years. Although interpreted languages allow for substantial reduction of software development time, they are often rejected due to performance concerns. In this paper we present an extension for the programming language Ruby, called HornetsEye, which facilitates the development of real-time machine vision algorithms within Ruby. Apart from providing integration of crucial libraries for input and output, HornetsEye provides fast native implementations (compiled code) for a generic set of array operators. Different array operators were compared with equivalent implementations in C++. Not only was it possible to achieve comparable real-time performance, but also to exceed the efficiency of the C++ implementation in several cases. Implementations of several algorithms were given to demonstrate how the array operators can be used to create concise implementations.</p

Effective one-component description of two-component Bose-Einstein condensate dynamics

We investigate dynamics in two-component Bose-Einstein condensates in the context of coupled Gross-Pitaevskii equations and derive results for the evolution of the total density fluctuations. Using these results, we show how, in many cases of interest, the dynamics can be accurately described with an effective one-component Gross-Pitaevskii equation for one of the components, with the trap and interaction coefficients determined by the relative differences in the scattering lengths. We discuss the model in various regimes, where it predicts breathing excitations, and the formation of vector solitons. An effective nonlinear evolution is predicted for some cases of current experimental interest. We then apply the model to construct quasi-stationary states of two-component condensates.Comment: 8 pages, 4 figure

STM Studies of Synthetic Peptide Monolayers

We have used scanning probe microscopy to investigate self-assembled monolayers of chemically synthesized peptides. We find that the peptides form a dense uniform monolayer, above which is found a sparse additional layer. Using scanning tunneling microscopy, submolecular resolution can be obtained, revealing the alpha helices which constitute the peptide. The nature of the images is not significantly affected by the incorporation of redox cofactors (hemes) in the peptides.Comment: 4 pages, 3 figures (4 gifs); to appear in the Proceedings of the XIIth Int. Winterschool on Electronic Properties of Novel Materials "Molecular Nanostructures", Kirchberg/Tyrol, Febr. 199

Preliminary Geologic Description PRAIRIE #1-A MAST

Three intervals of the Travis Peak Formation were cored in the Prairie #1 - A Mast well, Nacogdoches County, Texas. Core was recovered from 8,623.0 to 8,681.2 ft, 9,143.0 to 9,237.0 ft, and 9,930.0 to 9,991.5 ft. The top of the Travis Peak in this well is at 8,043 ft, so the core begins about 580 ft below the contact with the Sligo Formation.Bureau of Economic Geolog

Preliminary Geologic Description Ashland #1 S.F.O.T.

Two intervals of the Travis Peak Formation were cored in the Ashland #1 S.F.O.T. well, Nacogdoches County, Texas. The first interval ranges from 9,783.1 to 9,655.0 ft, and the second interval ranges from 10,083.9 to 10,155.2 ft. The top of the Travis Peak in this well is at 9,406 ft, so the core begins about 260 ft below the contact with the Sligo Formation.Bureau of Economic Geolog

Preliminary Geologic Description Arco #1 B. F. Phillips

Two intervals of the Travis Peak Formation were cored in the ARCO #1 B. F. Phillips well, Smith County, Texas. Core was recovered from 8,188 to 8,270 ft and from 8,367 to 8,395 ft. The top of the Travis Peak in this well is at 8,141 ft; therefore, the core begins about 50 ft below the contact with the Sligo Formation.Bureau of Economic Geolog

Preliminary Geologic Description Clayton W. Williams Jr. Sam Hughes #1

Two intervals of the Travis Peak Formation were cored in the Clayton Williams #1 Sam Hughes well, Panola County, Texas. Core was recovered from 6,834.0 to 6,851.7 ft and from 7,044.0 to 7,110.4 ft. The top of the Travis Peak in this well is at 6,830 ft, so the upper core begins a few feet below the contact with the Sligo Formation.Bureau of Economic Geolog

Preliminary Geologic Description Arkla Exploration T.P. Scott No.5

Three intervals of the Travis Peak Formation were cored in the Arkansas Louisiana Gas Company (Arkla) T. P. Scott No. 5 well, Waskom field, Harrison County, Texas. Core was recovered from 5,823.0 to 5,865.3 ft, 6,143.0 to 6,235.9 ft, and 7,413.0 to 7,523.0 ft. The top of the Travis Peak is at 5,841.5 ft (core depth), so 18.5 ft of carbonates from the Sligo Formation were recovered in the upper cored interval.Bureau of Economic Geolog

Preliminary Geologic Description Marshall Exploration Werner Sawmill No.5

Three intervals of the Travis Peak Formation were cored in the Marshall Exploration Werner Sawmill No. 5 well, Belle Bower field, Panola County, Texas. Core was recovered from 6,546.0 to 6,642.7 ft, 6,853.0 to 6,912.3 ft, and 7,049.0 to 7,141.1 ft. The top of the Travis Peak is at 6,478 ft so the core begins about 68 ft below the contact with the Sligo Formation.Bureau of Economic Geolog