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.

System and method for decoding and analyzing barcodes using a mobile device

Abstract: The present invention discloses a system and method for decoding barcodes using mobile device. Generally, the barcode image is acquired via a digital camera attached to the mobile device. After the barcode image has been acquired, software located on the mobile device enhances the barcode image and subsequently decodes the barcode information. The barcode information is then transmitted to a server via a wireless network. The server processes the barcode information and transmits media content related to the barcode back to the mobile device.

Color-encoded digital fringe projection technique for high-speed three-dimensional surface contouring

Abstract: A color-encoded digital fringe projection technique is proposed for high-speed 3-D surface contouring applications. in this technique, a color fringe pattern whose RGB components comprise three phase-shifted fringe patterns is created by software on a computer screen and then projected to an object by a novel computer-controlled digital projection system. The image of the object is captured by a digital camera positioned at an angle different from that of the projection system. The image is then separated into its RGB components, creating three phase-shifted images of the object. These three images are used to retrieve the 3-D surface contour of the object through the use of a phase wrapping and unwrapping algorithm. Only one image of the object is required to obtain the 3-D surface contour of the object. Thus contouring speed, limited only by the frame rate of the camera, can be dramatically increased as compared to that of the traditional phase-shifting techniques. The technique is especially useful in applications where the object being contoured is going through quasi-static or dynamic changes. The principle of the technique is described and some preliminary experimental results are presented.

Toward Real-World Single Image Super-Resolution: A New Benchmark and a New Model

Abstract: Most of the existing learning-based single image super-resolution (SISR) methods are trained and evaluated on simulated datasets, where the low-resolution (LR) images are generated by applying a simple and uniform degradation (i.e., bicubic downsampling) to their high-resolution (HR) counterparts. However, the degradations in real-world LR images are far more complicated. As a consequence, the SISR models trained on simulated data become less effective when applied to practical scenarios. In this paper, we build a real-world super-resolution (RealSR) dataset where paired LR-HR images on the same scene are captured by adjusting the focal length of a digital camera. An image registration algorithm is developed to progressively align the image pairs at different resolutions. Considering that the degradation kernels are naturally non-uniform in our dataset, we present a Laplacian pyramid based kernel prediction network (LP-KPN), which efficiently learns per-pixel kernels to recover the HR image. Our extensive experiments demonstrate that SISR models trained on our RealSR dataset deliver better visual quality with sharper edges and finer textures on real-world scenes than those trained on simulated datasets. Though our RealSR dataset is built by using only two cameras (Canon 5D3 and Nikon D810), the trained model generalizes well to other camera devices such as Sony a7II and mobile phones.

Source camera identification based on CFA interpolation

Abstract: In this work, we focus our interest on blind source camera identification problem by extending our results in the direction of M. Kharrazi et al. (2004). The interpolation in the color surface of an image due to the use of a color filter array (CFA) forms the basis of the paper. We propose to identify the source camera of an image based on traces of the proprietary interpolation algorithm deployed by a digital camera. For this purpose, a set of image characteristics are defined and then used in conjunction with a support vector machine based multi-class classifier to determine the originating digital camera. We also provide initial results on identifying source among two and three digital cameras.