Image scanner

An image scanner—often abbreviated to just scanner—is a device that optically scans images, printed text, handwriting or an object and converts it to a . Commonly used in offices are variations of the desktop flatbed scanner where the document is placed on a glass window for scanning. Hand-held scanners, where the device is moved by hand, have evolved from text scanning "wands" to 3D scanners used for industrial design, reverse engineering, test and measurement, orthotics, gaming and other applications. Mechanically driven scanners that move the document are typically used for large-format documents, where a flatbed design would be impractical. Modern scanners typically use a charge-coupled device (CCD) or a (CIS) as the image sensor, whereas drum scanners, developed earlier and still used for the highest possible image quality, use a photomultiplier tube (PMT) as the image sensor. A rotary scanner, used for high-speed document scanning, is a type of drum scanner that uses a CCD arr

Experimental Contribution to the Mechanics of Herringbone Grooved Journal Air Bearings

Ivan Ognjanovic

Gas Lubricated Herringbone Grooved Journal Bearings (HGJB) have long been used in equipment such as navigation systems, optical scanners for laser printers and high speed cameras and disk spindle for flyhead testers. All such applications are characterized by a relatively small size (journal diameter

EPFL2011

Alternative Search Techniques for Face Detection Using Location Estimation and Binary Features

Venkatesh Bala Subburaman

The sliding window approach is the most widely used technique to detect objects from an image. In the past few years, classifiers have been improved in many ways to increase the scanning speed. Apart from the classifier design (such as the cascade), the scanning speed also depends on a number of different factors (such as grid spacing, and scale at which the image is searched). Scanning grid spacing controls the number of subwindows being processed, thus controlling the speed of detection. When the scanning grid spacing is larger than the tolerance of the trained classifier it can suffer from low detections. In this thesis, we propose an alternative search technique, which can improve the detections when lesser number of subwindows are processed. First, we present a technique to reduce the number of miss detections while increasing the grid spacing when using the sliding window approach for object detection. This is achieved by using a small patch to predict the location of an object within a local search area. To achieve speed, it is necessary that the time taken for location prediction is comparable or better than the time it takes in average for the object classifier to reject a subwindow. We use binary features and a decision tree as it proved to be efficient for our application. In the process we also propose a variation of an existing binary feature (Ferns) with similar performance, and requires only half the number of pixel access when compared to Fern feature. We analyze the effect of patch size on location estimation and also evaluate our approach on several face databases. Experimental evaluation shows better detection rate and speed with our proposed approach for larger grid spacing (lesser number of subwindows) when compared to standard scanning technique. We also show that by using a simple interest point detector based on quantized gradient orientation, as the front-end to the proposed location estimation technique, we can achieve better performance even when fewer number of subwindows are processed. The interest points detected can be assumed as a non-regular grid compared to regular grid in the sliding window framework. A few image patches are sampled around an interest point for estimating the probable face location and further verified using a strong face classifier. Experiment results show that using an interest point detector can reduce the number of subwindows processed while maintaining a good detection rate.

EPFL2012

Alternative Search Techniques for Face Detection Using Location Estimation and Binary Features

Venkatesh Bala Subburaman

EPFL2012

High speed depth optical scanner

Experimental Contribution to the Mechanics of Herringbone Grooved Journal Air Bearings

Alternative Search Techniques for Face Detection Using Location Estimation and Binary Features

Alternative Search Techniques for Face Detection Using Location Estimation and Binary Features

High speed depth optical scanner

Experimental Contribution to the Mechanics of Herringbone Grooved Journal Air Bearings