AN INVENTORY OF PHOTOGRAPHS OF ZINC ELECTRODEPOSITED FROM ACID ELECTROLYTES

Electrodeposition of zinc from acid electrolytes has been studied by several investigators in this laboratory. A large number of zinc deposits have been observed and photographs (SEM, micrographs, experimental equipment, and line drawings) have been prepared over the years 1976-1983. These photos are compiled in this LBL report to facilitate their future use by others. The tables in this report list the experimental conditions and corresponding identification numbers of photographs that are on file in the Photography Services Laboratory at the Lawrence Berkeley Laboratory. Several samples of these zinc deposits are shown

AN INVENTORY OF PHOTOGRAPHS OF ZINC ELECTRODEPOSITED FROM ACID ELECTROLYTES

Electrodeposition of zinc from acid electrolytes has been studied by several investigators in this laboratory. A large number of zinc deposits have been observed and photographs (SEM, micrographs, experimental equipment, and line drawings) have been prepared over the years 1976-1983. These photos are compiled in this LBL report to facilitate their future use by others. The tables in this report list the experimental conditions and corresponding identification numbers of photographs that are on file in the Photography Services Laboratory at the Lawrence Berkeley Laboratory. Several samples of these zinc deposits are shown

Robust learning from normals for 3D face recognition

We introduce novel subspace-based methods for learning from the azimuth angle of surface normals for 3D face recognition. We show that the normal azimuth angles combined with Principal Component Analysis (PCA) using a cosine-based distance measure can be used for robust face recognition from facial surfaces. The proposed algorithms are well-suited for all types of 3D facial data including data produced by range cameras (depth images), photometric stereo (PS) and shade-from-X (SfX) algorithms. We demonstrate the robustness of the proposed algorithms both in 3D face reconstruction from synthetically occluded samples, as well as, in face recognition using the FRGC v2 3D face database and the recently collected Photoface database where the proposed method achieves state-of-the-art results. An important aspect of our method is that it can achieve good face recognition/verification performance by using raw 3D scans without any heavy preprocessing (i.e., model fitting, surface smoothing etc.). © 2012 Springer-Verlag

A review of recent advances in 3D ear and expression invariant face biometrics

Biometric-based human recognition is rapidly gaining popularity due to breaches of traditional security systems and the lowering cost of sensors. The current research trend is to use 3D data and to combine multiple traits to improve accuracy and robustness. This article comprehensively reviews unimodal and multimodal recognition using 3D ear and face data. It covers associated data collection, detection, representation, and matching techniques and focuses on the challenging problem of expression variations. All the approaches are classified according to their methodologies. Through the analysis of the scope and limitations of these techniques, it is concluded that further research should investigate fast and fully automatic ear-face multimodal systems robust to occlusions and deformations