Showing papers on "Digital camera published in 2015"

Imaging with a small number of photons

Abstract: Low-light-level imaging techniques have application in many diverse fields, ranging from biological sciences to security. A high-quality digital camera based on a multi-megapixel array will typically record an image by collecting of order 105 photons per pixel, but by how much could this photon flux be reduced? In this work we demonstrate a single-photon imaging system based on a time-gated intensified camera from which the image of an object can be inferred from very few detected photons. We show that a ghost-imaging configuration, where the image is obtained from photons that have never interacted with the object, is a useful approach for obtaining images with high signal-to-noise ratios. The use of heralded single photons ensures that the background counts can be virtually eliminated from the recorded images. By applying principles of image compression and associated image reconstruction, we obtain high-quality images of objects from raw data formed from an average of fewer than one detected photon per image pixel.

Investigating the geomorphological potential of freely available and accessible structure-from-motion photogrammetry using a smartphone

Abstract: We test the acquisition of high-resolution topographic and terrain data using hand-held smartphone technology, where the acquired images can be processed using technology freely available to the research community. This is achieved by evaluating the quality of digital terrain models (DTM) of a river bank and an Alpine alluvial fan generated with a fully automated, free-to-use, structure-from-motion package and a smartphone integrated camera (5 megapixels) with terrestrial laser scanning (TLS) data used to provide a benchmark. To evaluate this approach a 16.2-megapixel digital camera and an established, commercial, close-range and semi-automated software are also employed, and the product of the four combinations of the two types of cameras and software are compared. Results for the river bank survey demonstrate that centimetre-precision DTMs can be achieved at close range (10 m or less), using a smartphone camera and a fully automated package. Results improve to sub-centimetre precision with either higher-resolution images or by applying specific post-processing techniques to the smartphone DTMs. Application to an entire Alpine alluvial fan system shows the degradation of precision scales linearly with image scale, but that (i) the expected level of precision remains and (ii) difficulties in separating vegetation and sediment cover within the results are similar to those typically found when using other photo-based techniques and laser scanning systems. Copyright © 2014 John Wiley & Sons, Ltd.

Smartphone Irrigation Sensor

Abstract: An automated irrigation sensor was designed and implemented to use in agricultural crops. The sensor uses a smartphone to capture and process digital images of the soil nearby the root zone of the crop, and estimates optically the water contents. The sensor is confined in a chamber under controlled illumination and buried at the root level of the plants. An Android App was developed in the smartphone to operate directly the computing and connectivity components, such as the digital camera and the Wi-Fi network. The mobile App wakes up the smartphone, activating the device with user-defined parameters. Then, the built-in camera takes a picture of the soil through an antireflective glass window and an RGB to gray process is achieved to estimate the ratio between wet and dry area of the image. After the Wi-Fi connection is enabled, the ratio is transmitted via a router node to a gateway for control an irrigation water pump. Finally, the App sets the smartphone into the sleep mode to preserve its energy. The sensor is powered by rechargeable batteries, charged by a photovoltaic panel. The smartphone irrigation sensor was evaluated in a pumpkin crop field along 45 days. The experimental results show that the use of smartphones as an irrigation sensor could become a practical tool for agriculture.

Forensic Camera Model Identification

Abstract: This chapter presents an overview of the state of the art of technical means to achieve camera model identification. It starts with an introduction to forensic source identification. The chapter deals with a specific case of digital camera model identification. It comments on suitable image datasets for setting up practical algorithms, the foundations, and focuses on problems that arise in identification scenarios with unknown camera models. The chapter explains the connections between camera model identification and device identification. It talks about the open set camera model identification that poses an inherent challenge to the widely used multi-class support vector machines (SVMs), as they always assign a test sample to one of the trained classes. The role of model-specific characteristics in device-level identification is discussed. As forensic camera model identification finds applications in practical investigations, a more explicit treatment of the different types of artifact interdependencies will gain more relevance.

System and method for controlling a camera based on processing an image captured by other camera

Abstract: A device comprises a first digital camera having a first center line of sight and a second digital camera having a second center line of sight that is parallel and opposing the first camera. A method for controlling the first camera based on estimating the angular deviation between a person gaze direction and the line of sight of the first digital camera. A human face is detected in an image captured as an image file by the second digital camera, using a face detection algorithm. An angular deviation α is estimated, defined between the second center line of sight and an imaginary line from the second camera to the detected human face based on the captured image, and an angular deviation β is estimated, defined between the imaginary line from the second camera to the detected face and the human face gaze direction based on the captured image.

2D LiDAR and camera fusion in 3D modeling of indoor environment

Abstract: Detailed 3D modeling of indoor scene has become an important topic in many research fields It can provide extensive information about the environment and boost various location based services, such as interactive gaming and indoor navigation This paper presents an indoor scene construction approach using 2D line-scan LiDAR and entry-level digital camera Both devices are mounted rigidly on a robotic servo, which sweeps vertically to cover the third dimension Fiducial target based extrinsic calibration is applied to acquire transformation matrices between LiDAR and camera Based on the transformation matrix, we perform registration to fuse the color images from the camera with the 3D points cloud from the LiDAR The whole system setup has much lower cost as compared to systems using 3D LiDAR and omnidirectional camera Using pre-calculated transformation matrices instead of feature extraction techniques such as SIFT or SURF in registration gives better fusion result and lower computational complexity The experiments carried out in office building environment show promising results of our approach

Digital camera having low power capture mode

Abstract: A digital camera system providing a low-power image capture mode includes an image capture system, an image display and a power management system. The power management system is used to provide a normal image capture mode wherein captured digital images are displayed on the image display as they are captured, and a low-power image capture mode wherein captured digital images are not displayed on the image display as they are captured. A user interface includes a first user control for selecting between the normal image capture mode and the low-power image capture mode, and a second user control for initiating a video capture operation. The system is configured such that if the first user control is activated while a digital video is being captured, the power management system switches between the normal image capture mode and the low-power image capture mode without interrupting the video capture operation.

Full-color structured illumination optical sectioning microscopy

Abstract: In merits of super-resolved resolution and fast speed of three-dimensional (3D) optical sectioning capability, structured illumination microscopy (SIM) has found variety of applications in biomedical imaging. So far, most SIM systems use monochrome CCD or CMOS cameras to acquire images and discard the natural color information of the specimens. Although multicolor integration scheme are employed, multiple excitation sources and detectors are required and the spectral information is limited to a few of wavelengths. Here, we report a new method for full-color SIM with a color digital camera. A data processing algorithm based on HSV (Hue, Saturation, and Value) color space is proposed, in which the recorded color raw images are processed in the Hue, Saturation, Value color channels, and then reconstructed to a 3D image with full color. We demonstrated some 3D optical sectioning results on samples such as mixed pollen grains, insects, micro-chips and the surface of coins. The presented technique is applicable to some circumstance where color information plays crucial roles, such as in materials science and surface morphology.

Imaging and peripheral enhancements for mobile devices

Abstract: An image enhancer device for use with an associated mobile electronic device having a digital camera. The image enhancer device includes an image manipulator coupled to a first region of a housing and configured to modify an optical path of the digital camera; an aimer having an aiming element configured to direct at least one aiming light beam towards an object of interest; an illuminator having an illumination element configured to direct at least one illumination light beam from the housing towards the object of interest; and electronics allowing for communication between the image enhancer device and the associated mobile electronic device. The image enhancer device forms a scan angle relative to a field of view of the digital camera of the mobile electronic device and allows for bar code imaging and/or native image processing with the digital camera of the associated mobile electronic device.

Can We Trust the Use of Smartphone Cameras in Clinical Practice? Laypeople Assessment of Their Image Quality

Abstract: Background: Smartphone cameras are rapidly being introduced in medical practice, among other devices for image-based teleconsultation Little is known, however, about the actual quality of the images taken, which is the object of this study Materials and Methods: A series of nonclinical objects (from three broad categories) were photographed by a professional photographer using three smartphones (iPhone® 4 [Apple, Cupertino, CA], Samsung [Suwon, Korea] Galaxy S2, and BlackBerry® 9800 [BlackBerry Ltd, Waterloo, ON, Canada]) and a digital camera (Canon [Tokyo, Japan] Mark II) In a Web survey a convenience sample of 60 laypeople “blind” to the types of camera assessed the quality of the photographs, individually and best overall We then measured how each camera scored by object category and as a whole and whether a camera ranked best using a Mann–Whitney U test for 2×2 comparisons Results: There were wide variations between and within categories in the quality assessments for all four cameras The iPhone had the highest proportion of images individually evaluated as good, and it also ranked best for more objects compared with other cameras, including the digital one The ratings of the Samsung or the BlackBerry smartphone did not significantly differ from those of the digital camera Conclusions: Whereas one smartphone camera ranked best more often, all three smartphones obtained results at least as good as those of the digital camera Smartphone cameras can be a substitute for digital cameras for the purposes of medical teleconsulation

From Photon to Pixel: The Digital Camera Handbook

Abstract: The digital camera conceals remarkable technological innovations that affect the formation of the image, the color representation or automated measurements and settings. ** From photon to pixel photon ** describes the device both from the point of view of the physics of the phenomena involved, as technical components and software it uses. Based on the perceptual properties of the visual system as well as on standard transmission and representation, analyzes the solutions to meet the demands of the photographer on the development, contrast, white balance or stabilization of image. The advanced architectures adopted in mobile phones and developments of computational photography are also presented, foreshadowing the features of the future device.

In-flight photogrammetric camera calibration and validation via complementary lidar

Abstract: This research assumes lidar as a reference dataset against which in-flight camera system calibration and validation can be performed. The methodology utilises a robust least squares surface matching algorithm to align a dense network of photogrammetric points to the lidar reference surface, allowing for the automatic extraction of so-called lidar control points (LCPs). Adjustment of the photogrammetric data is then repeated using the extracted LCPs in a self-calibrating bundle adjustment with additional parameters. This methodology was tested using two different photogrammetric datasets, a Microsoft UltraCamX large format camera and an Applanix DSS322 medium format camera. Systematic sensitivity testing explored the influence of the number and weighting of LCPs. For both camera blocks it was found that when the number of control points increase, the accuracy improves regardless of point weighting. The calibration results were compared with those obtained using ground control points, with good agreement found between the two.

Low-Light Image Enhancement Using Adaptive Digital Pixel Binning

Abstract: This paper presents an image enhancement algorithm for low-light scenes in an environment with insufficient illumination. Simple amplification of intensity exhibits various undesired artifacts: noise amplification, intensity saturation, and loss of resolution. In order to enhance low-light images without undesired artifacts, a novel digital binning algorithm is proposed that considers brightness, context, noise level, and anti-saturation of a local region in the image. The proposed algorithm does not require any modification of the image sensor or additional frame-memory; it needs only two line-memories in the image signal processor (ISP). Since the proposed algorithm does not use an iterative computation, it can be easily embedded in an existing digital camera ISP pipeline containing a high-resolution image sensor.

System and Method of Video Wall Setup and Adjustment Using Automated Image Analysis

Abstract: A system is disclosed for identifying, placing and configuring a physical arrangement of a plurality of displays via image analysis of captured digital camera images depicting unique configuration images output to said displays to facilitate uniform operation of said plurality of displays as a single display area for example as a video wall. The system pairs and configures displays depicted in the captured images to individual displays within the physical arrangement through controlling and analyzing of the output of said displays captured in said images. A method and computer readable medium are also disclosed that operate in accordance with the system.

Fragile sensor fingerprint camera identification

Abstract: We study digital camera identification based on sensor noise in an adversarial environment with asymmetries. We focus on fingerprint-copy attacks, where the attacker has access to JPEG images only, while the defender may leverage uncompressed images. This leads to the notion of fragile sensor fingerprints that are only available to the defender but do not survive lossy compression. Experiments with seven different cameras suggest a highly reliable detection of the attack as long as no high-quality images are shared with the public.

Adaptive exposure estimation for high dynamic range imaging applied to natural scenes and daylight skies

Abstract: Digital imaging of natural scenes and optical phenomena present on them (such as shadows, twilights, and crepuscular rays) can be a very challenging task because of the range spanned by the radiances impinging on the capture system. We propose a novel method for estimating the set of exposure times (bracketing set) needed to capture the full dynamic range of a scene with high dynamic range (HDR) content. The proposed method is adaptive to scene content and to any camera response and configuration, and it works on-line since the exposure times are estimated as the capturing process is ongoing. Besides, it requires no a priori information about scene content or radiance values. The resulting bracketing sets are minimal in the default method settings, but the user can set a tolerance for the maximum percentage of pixel population that is underexposed or saturated, which allows for a higher number of shots if a better signal-to-noise ratio (SNR) in the HDR scene is desired. This method is based on the use of the camera response function that is needed for building the HDR radiance map by stitching together several differently exposed low dynamic range images of the scene. The use of HDR imaging techniques converts our digital camera into a tool for measuring the relative radiance outgoing from each point of the scene, and for each color channel. This is important for accurate characterization of optical phenomena present in the atmosphere while not suffering any loss of information due to its HDR. We have compared our method with the most similar one developed so far [IEEE Trans. Image Process.17, 1864 (2008)]. Results of the experiments carried out for 30 natural scenes show that our proposed method equals or outperforms the previously developed best approach, with less shots and shorter exposure times, thereby asserting the advantage of being adaptive to scene content for exposure time estimation. As we can also tune the balance between capturing time and the SNR in our method, we have compared its SNR performance against that of Barakat's method as well as against a ground-truth HDR image of maximum SNR. Results confirm the success of the proposed method in exploiting its tunability to achieve the desired balance of total Δt and SNR.

Low-cost single-camera imaging system for aerial applicators

Abstract: Agricultural aircraft provide a readily available and versatile platform for airborne remote sensing. Although various airborne imaging systems are available, most of these systems are either too expensive or too complex to be of practical use for day-to-day aerial application operations. The objective of this study was to develop a low-cost, user-friendly imaging system that can be easily installed on aerial applicators. An imaging system was assembled using off-the-shelf electronics. The system consisted of a digital camera to capture color images, a GPS receiver to geotag images, a video monitor to view live images, and a remote control to trigger the camera. The camera was attached to an aerial applicator and the GPS unit and video monitor were installed in the cockpit. The parameters of the camera were optimized to acquire images under various altitudes, speeds, and ground cover conditions. Geotagged images taken from individual sites or large areas were viewed and mosaicked together using free and inexpensive software. Aerial applicators can assemble such a system and use it to generate additional revenues from remote sensing services. Analysis of sample images has shown that the imaging system has potential for crop condition assessment and pest detection.

Multi-data fusion forest fire intelligent recognition system and method

Abstract: The invention discloses a multi-data fusion forest fire intelligent recognition system. The system includes a thermal infrared imager, a digital camera, an ultrasonic meteorological station, a geographic information system and an upper computer, wherein the thermal infrared imager, the digital camera, the ultrasonic meteorological station and the geographic information system are connected with the upper computer; and the upper computer is provided with an artificial neural network and a fuzzy expert system, the artificial neural system analyzes infrared images collected by the thermal infrared imager and visible light images collected by the digital camera and transmits analyzed data to the fuzzy expert system for calculation of the probability of a forest fire, the ultrasonic meteorological station provides meteorological data of a forest, and the geographic information system provides geographic information. The invention provides a multi-data fusion forest fire intelligent recognition system and method, and the method fuses various data to make forest fire predictions, and can remarkably reduce a false recognition rate of forest fires, improve operating efficiency of the system, and reduce labor intensity of workers.

Ocr accuracy improvement on document images through a novel pre-processing approach

Abstract: Digital camera and mobile document image acquisition are new trends arising in the world of Optical Character Recognition and text detection. In some cases, such process integrates many distortions and produces poorly scanned text or text-photo images and natural images, leading to an unreliable OCR digitization. In this paper, we present a novel nonparametric and unsupervised method to compensate for undesirable document image distortions aiming to optimally improve OCR accuracy. Our approach relies on a very efficient stack of document image enhancing techniques to recover deformation of the entire document image. First, we propose a local brightness and contrast adjustment method to effectively handle lighting variations and the irregular distribution of image illumination. Second, we use an optimized greyscale conversion algorithm to transform our document image to greyscale level. Third, we sharpen the useful information in the resulting greyscale image using Un-sharp Masking method. Finally, an optimal global binarization approach is used to prepare the final document image to OCR recognition. The proposed approach can significantly improve text detection rate and optical character recognition accuracy. To demonstrate the efficiency of our approach, an exhaustive experimentation on a standard dataset is presented

An autofocus heuristic for digital cameras based on supervised machine learning

Abstract: Digital cameras are equipped with passive autofocus mechanisms where a lens is focused using only the camera's optical system and an algorithm for controlling the lens. The speed and accuracy of the autofocus algorithm are crucial to user satisfaction. In this paper, we address the problems of identifying the global optimum and significant local optima (or peaks) when focusing an image. We show that supervised machine learning techniques can be used to construct a passive autofocus heuristic for these problems that out-performs an existing hand-crafted heuristic and other baseline methods. In our approach, training and test data were produced using an offline simulation on a suite of 25 benchmarks and correctly labeled in a semi-automated manner. A decision tree learning algorithm was then used to induce an autofocus heuristic from the data. The automatically constructed machine-learning-based (ml-based) heuristic was compared against a previously proposed hand-crafted heuristic for autofocusing and other baseline methods. In our experiments, the ml-based heuristic had improved speed--reducing the number of iterations needed to focus by 37.9 % on average in common photography settings and 22.9 % on average in a more difficult focus stacking setting--while maintaining accuracy.

3d point cloud model colorization by dense registration of digital images

Abstract: Architectural heritage is a historic and artistic property which has to be protected, preserved, restored and must be shown to the public. Modern tools like 3D laser scanners are more and more used in heritage documentation. Most of the time, the 3D laser scanner is completed by a digital camera which is used to enrich the accurate geometric informations with the scanned objects colors. However, the photometric quality of the acquired point clouds is generally rather low because of several problems presented below. We propose an accurate method for registering digital images acquired from any viewpoints on point clouds which is a crucial step for a good colorization by colors projection. We express this image-to-geometry registration as a pose estimation problem. The camera pose is computed using the entire images intensities under a photometric visual and virtual servoing (VVS) framework. The camera extrinsic and intrinsic parameters are automatically estimated. Because we estimates the intrinsic parameters we do not need any informations about the camera which took the used digital image. Finally, when the point cloud model and the digital image are correctly registered, we project the 3D model in the digital image frame and assign new colors to the visible points. The performance of the approach is proven in simulation and real experiments on indoor and outdoor datasets of the cathedral of Amiens, which highlight the success of our method, leading to point clouds with better photometric quality and resolution.

Camera for an aerosol delivery device

Abstract: An aerosol delivery device includes a housing, a cartridge coupled to the housing, a control component contained within the housing, and a camera system including a digital camera on the housing. The control component is configured to control operation of the aerosol delivery device in response to detection of airflow through at least a portion of the housing or cartridge. The digital camera is configured to capture images of an object or scene in a field of view thereof, with the images being transferable locally to a memory configured to store the images, or externally to a computing device configured to store or display the images.

Systems and methods for sizing shoes

Abstract: Capturing three-dimensional images of feet and arraying them against vast databases of stored shoe data enables better developed matching with desired fittings than conventional systems. Smartphone/iPhone/digital camera and related interface tools supported by proprietary data streams and engines recommend better shoe choices from plethoric offerings updated continually and based upon legacy shoe data along with new ways to compare and select shoes.

Detection and Recognition of Illegally Parked Vehicles Based on an Adaptive Gaussian Mixture Model and a Seed Fill Algorithm

Abstract: In this paper, we present an algorithm for the detection of illegally parked vehicles based on a combination of some image processing algorithms. A digital camera is fixed in the illegal parking region to capture the video frames. An adaptive Gaussian mixture model (GMM) is used for background subtraction in a complex environment to identify the regions of moving objects in our test video. Stationary objects are detected by using the pixel-level features in time sequences. A stationary vehicle is detected by using the local features of the object, and thus, information about illegally parked vehicles is successfully obtained. An automatic alarm system can be utilized according to the different regulations of different illegal parking regions. The results of this study obtained using a test video sequence of a real-time traffic scene show that the proposed method is effective.

Methodology for generating high fidelity digital zoom for mobile phone cameras

Abstract: A mobile device includes an embedded digital camera that is configured to capture a burst of N images. The mobile device includes processing circuitry comprising a registration module configured to, for each image within the burst of images: analyze an amount of warp of the image and generate a set of affine matrices indicating the amount of warp of the image. The processing circuitry includes a High Fidelity Interpolation block configured to, for each image within the burst of images: perform affine transformation using the set of affine matrices associated with the image, apply an aliasing-retaining interpolation filter, and implement rotation transformation and sub-pixel shifts, yielding an interpolated image. The processing circuitry includes a blending module configured to receive the N interpolated images and blend the N interpolated images into a single-blended image having a user-selected digital zoom ratio.

Stain detection and classification method and device for sensor of digital camera

Abstract: The invention discloses a stain detection method for a sensor of a digital camera, and a method and a device for classifying the sensor of the camera based on the detection method, wherein the method comprises the following steps: (1) inputting original image data and obtaining luminance component via interpolation, (2) low-pass filtering, (3) edge enhancement, (4) band-pass filtering, (5) image binaryzation operation and morphological dilation, (6) connectivity area abstraction, (7) marking stain in an original image, (8) classifying the sensor and outputting image level. The invention is divided as two function modules which are used for detecting the stain and classifying the sensor. A contiguous item of a classification decision function is from features such as quantity, area, and color depth of the stain detected in a shooting image. The method and the device of the invention is simple and efficient and can be used for fast detecting stain position on the sensor and carrying out accurate level evaluation to current sensor according to the feature of theses stains.

Precision luxmeter methods for digital cameras to quantify colors in uncontrolled lighting environments

Abstract: In one embodiment, a diagnostic system for biological samples is disclosed. The diagnostic system includes a diagnostic instrument, and a portable electronic device. The diagnostic instrument has a reference color bar and a plurality of chemical test pads to receive a biological sample. The portable electronic device includes a digital camera to capture a digital image of the diagnostic instrument in uncontrolled lightning environments, a sensor to capture illuminance of a surface of the diagnostic instrument, a processor coupled to the digital camera and sensor to receive the digital image and the illuminance, and a storage device coupled to the processor. The storage device stores instructions for execution by the processor to process the digital image and the illuminance, to normalize colors of the plurality of chemical test pads and determine diagnostic test results in response to quantification of color changes in the chemical test pads.

Pull rod type digital camera

Abstract: This patent application relates to a digital camera field, in particular, to a kind of pull-rod type digital camera The pull-rod type digital camera includes a shooting assembly and a control assembly The shooting assembly includes a camera, and the digital camera further includes a telescopic rod One end of the telescopic rod is arranged movably inside the control assembly, and the other end is rotationally connected with the shooting assembly, through which the shooting assembly can be separated from the control assembly to a certain distance when stretching the telescopic rod, and it is convenient to take a selfie and carry out other operations by rotating the shooting assembly to a proper position