Digital camera

About: Digital camera is a research topic. Over the lifetime, 12169 publications have been published within this topic receiving 137431 citations. The topic is also known as: digicam & digital still camera.

Method and apparatus for mosaic image construction

Abstract: A method of constructing an image mosaic comprising the steps of selecting source images, aligning the source images, selecting source segments, enhancing the images, and merging the images to form the image mosaic is disclosed. An apparatus for constructing an image mosaic comprising means for selecting source images (102), means for aligning the source images (103), means for selecting source image segments (104), means for enhancing the images (105), and means for merging (106) the images to form the image mosaic is also disclosed. The process may be performed automatically by the system or may be guided interactively by a human operator. Applications include the construction of photographic quality prints from video and digital camera images.

Digital camera with apparatus for authentication of images produced from an image file

Abstract: A digital camera equipped with a processor for authentication of images produced from an image file taken by the digital camera is provided. The digital camera processor has embedded therein a private key unique to it, and the camera housing has a public key that is so uniquely related to the private key that digital data encrypted with the private key may be decrypted using the public key. The digital camera processor comprises means for calculating a hash of the image file using a predetermined algorithm, and second means for encrypting the image hash with the private key, thereby producing a digital signature. The image file and the digital signature are stored in suitable recording means so they will be available together. Apparatus for authenticating the image file as being free of any alteration uses the public key for decrypting the digital signature, thereby deriving a secure image hash identical to the image hash produced by the digital camera and used to produce the digital signature. The authenticating apparatus calculates from the image file an image hash using the same algorithm as before. By comparing this last image hash with the secure image hash, authenticity of the image file is determined if they match. Other techniques to address time-honored methods of deception, such as attaching false captions or inducing forced perspectives, are included.

The trustworthy digital camera: restoring credibility to the photographic image

Abstract: The trustworthy digital camera is an application of existing technology toward the solution of an evermore-troubling social problem, the eroding credibility of the photographic image. Although it will always be possible to lie with a photograph (using such time-honored techniques as false perspective and misleading captions), this proposed device will prevent the explosion of very capable personal computers from driving up the incidence of doctored photographs being passed off as truth. A solution to this problem comes from the proposed digital signature standard (DSS), which incorporates modern cryptographic techniques to authenticate electronic mail messages. >

A quantitative study of three-dimensional Lagrangian particle tracking algorithms

Abstract: A neural network particle finding algorithm and a new four-frame predictive tracking algorithm are proposed for three-dimensional Lagrangian particle tracking (LPT). A quantitative comparison of these and other algorithms commonly used in three-dimensional LPT is presented. Weighted averaging, one-dimensional and two-dimensional Gaussian fitting, and the neural network scheme are considered for determining particle centers in digital camera images. When the signal to noise ratio is high, the one-dimensional Gaussian estimation scheme is shown to achieve a good combination of accuracy and efficiency, while the neural network approach provides greater accuracy when the images are noisy. The effect of camera placement on both the yield and accuracy of three-dimensional particle positions is investigated, and it is shown that at least one camera must be positioned at a large angle with respect to the other cameras to minimize errors. Finally, the problem of tracking particles in time is studied. The nearest neighbor algorithm is compared with a three-frame predictive algorithm and two four-frame algorithms. These four algorithms are applied to particle tracks generated by direct numerical simulation both with and without a method to resolve tracking conflicts. The new four-frame predictive algorithm with no conflict resolution is shown to give the best performance. Finally, the best algorithms are verified to work in a real experimental environment.

DSLR-Quality Photos on Mobile Devices with Deep Convolutional Networks

Abstract: Despite a rapid rise in the quality of built-in smartphone cameras, their physical limitations – small sensor size, compact lenses and the lack of specific hardware, – impede them to achieve the quality results of DSLR cameras. In this work we present an end-to-end deep learning approach that bridges this gap by translating ordinary photos into DSLR-quality images. We propose learning the translation function using a residual convolutional neural network that improves both color rendition and image sharpness. Since the standard mean squared loss is not well suited for measuring perceptual image quality, we introduce a composite perceptual error function that combines content, color and texture losses. The first two losses are defined analytically, while the texture loss is learned in an adversarial fashion. We also present DPED, a large-scale dataset that consists of real photos captured from three different phones and one high-end reflex camera. Our quantitative and qualitative assessments reveal that the enhanced image quality is comparable to that of DSLR-taken photos, while the methodology is generalized to any type of digital camera.