Tilt Correction Method Research Articles

A Study of the Intersection of Traditional Calligraphy and Digital Media Art

Abstract As a classic representative of traditional culture, Chinese calligraphy art has more and more obvious advantages in today’s digital media art creation. In this paper, the calligraphic text image is binarized by the OTSU method, the image enhancement is realized by linear gray value stretching, and the optimal tilt correction method is used to preprocess the traditional calligraphic text image and make a font library. Based on the data from the calligraphy font library, an immersive digital interactive context of traditional calligraphy is designed using digital media art. Pix2Pix network is introduced to combine with the PatchGAN network to establish a style migration network for traditional calligraphy text images, and three different types of loss functions are designed to ensure the accurate generation of traditional calligraphy text. The L1 loss of this paper’s model in generating traditional calligraphy characters is only 0.0359 at the lowest, the similarity values of the generated samples of calligraphy characters are mainly between 90% and 96%, and the maximum error of the relative position and relative size of the radicals is only 1.18%. The average value of the G2R indicator for the users’ images of calligraphic characters was 75.23%, and 89.86% of the users indicated that they were basically satisfied with the immersive interactive context of traditional calligraphy. Traditional calligraphy can achieve digital transformation and provide audiences with more diverse cultural experiences by relying on digital media art.

An Offline EP Test Tube Positioning Tilt Correction Algorithm Based on Lightweight Yolov4

As an infrastructure of biochemical laboratories, EP tube label plays a significant role in information extraction to meet the limitations of computing power in offline devices and solve the problem that the EP tube label cannot be accurately identified before identification because the label belongs to multi-angle random placement. This paper proposes a light-weight neural network YOLOv4-tiny-ECA to position tubes and a tilt correction method based on Hough transform. First, the EP tube rack is roughly positioned based on the diffuse filling algorithm combined with digital morphological corrosion, and then the EP tubes in the rack are precisely positioned using the light-weight YOLO target detection algorithm combined with the attention mechanism. Next, the baseline is added to the label as the basis for determining the tilt angle. For the valid target, the baseline is extracted using the Hough transform and the tilt angle is calculated by vector fork multiplication. Finally, baseline is removed using image processing algorithm for better recognition results. Our results show that the light-weight YOLO algorithm reduces the network parameters by 56% and computation by 55% while keeping the accuracy rate largely unchanged, the offline positioning tilt correction method can achieve 98.8% accuracy and 0.076[Formula: see text]s processing speed for a single test tube on average, which meets the real-time requirement.

Investigating the effect of oblique image acquisition on the accuracy of QSM and a robust tilt correction method.

Quantitative susceptibility mapping (QSM) is used increasingly for clinical research where oblique image acquisition is commonplace, but its effects on QSM accuracy are not well understood. The QSM processing pipeline involves defining the unit magnetic dipole kernel, which requires knowledge of the direction of the main magnetic field with respect to the acquired image volume axes. The direction of is dependent on the axis and angle of rotation in oblique acquisition. Using both a numerical brain phantom and in vivo acquisitions in 5 healthy volunteers, we analyzed the effects of oblique acquisition on magnetic susceptibility maps. We compared three tilt-correction schemes at each step in the QSM pipeline: phase unwrapping, background field removal and susceptibility calculation, using the RMS error and QSM-tuned structural similarity index. Rotation of wrapped phase images gave severe artifacts. Background field removal with projection onto dipole fields gave the most accurate susceptibilities when the field map was first rotated into alignment with . Laplacian boundary value and variable-kernel sophisticated harmonic artifact reduction for phase data background field removal methods gave accurate results without tilt correction. For susceptibility calculation, thresholded k-space division, iterative Tikhonov regularization, and weighted linear total variation regularization, all performed most accurately when local field maps were rotated into alignment with before susceptibility calculation. For accurate QSM, oblique acquisition must be taken into account. Rotation of images into alignment with should be carried out after phase unwrapping and before background-field removal. We provide open-source tilt-correction code to incorporate easily into existing pipelines: https://github.com/o-snow/QSM_TiltCorrection.git.

Research on Water-Level Recognition Method Based on Image Processing and Convolutional Neural Networks

Water level dynamics in catchment-scale rivers is an important factor for surface water studies. Manual measurement is highly accurate but inefficient. Using automatic water level sensors has disadvantages such as high cost and difficult maintenance. In this study, a water level recognition method based on digital image processing technology and CNN is proposed. For achieving batch segmentation of source images, the coordinates of the water ruler region in the source image and characters’ region and the scale lines’ region on the ruler are obtained by using image processing algorithms such as grayscale processing, edge detection, and the tilt correction method based on Hough-transform and morphological operations. The CNN is then used to identify the value of digital characters. Finally, the water level value is calculated according to the mathematical relationship between the number of scale lines detected by pixel traversal in the binarized image and the value of digital characters. This method is used to identify the water levels of the water ruler images collected in the Hulu watershed of the Qilian Mountains in Northwest China. The results show that the accuracy compared with the actual measured water level reached 94.6% and improved nearly 24% compared to the template matching algorithm. With high accuracy, low cost, and easy deployment and maintenance, this method can be applied to water level monitoring in mountainous rivers, providing an effective tool for watershed hydrology research and water resources management.

TILT CORRECTION OF ONBOARD DRONE IRRADIANCE MEASUREMENTS – EVALUATION OF HYPERSPECTRAL METHODS

Abstract. An accurate onboard irradiance measurement on drones is a requirement direct reflectance transformation of aerial images and remote sensing data without use of on-ground reference targets. One of the major error sources in onboard irradiance measurement is the effect of sensor tilt to the observed irradiances. In this paper/presentation, we will present an intercomparison of two methods: the FGI AIRS method and the Köppl method. Both methods require an irradiance sensor with good cosine response and IMU system providing accurate tilt angle for each irradiance measurement. Additionally to this, the AIRS method requires special hardware with multiple tilted irradiance sensors, which effectively allow interpolation of a virtual horizontal sensor. The Köppl method requires the irradiance sensor to be a spectral sensor, which allows the direct and diffuse fractions of irradiance spectrum to be deducted from shape of the measured spectrum using the spectral unmixing between direct and diffuse spectrum shapes. We present a field experiment where the AIRS sensor was flown in a typical mapping pattern flight and evaluate the tilt correction methods during it. During a fully sunny period of the flight, the standard deviations of the irradiances was ±6.4% for the uncorrected tilted irradiances, ±1.8% for the AIRS method, and ±2.0% for the Köppl method. The data shows that an accurate irradiance measurement onboard a drone is feasible using a well-calibrated irradiance sensor system and both methods are capable to produce quite similar results.

Improvement of spatial resolution by tilt correction in near-field scanning microwave microscopy

The limitation of mechanical manufacturing will result in a small tilt angle of the sample stage in the horizontal direction, which decreases the spatial resolution of imaging in near-field scanning microwave microscopy (NSMM). In this paper, we focus on the tilt correction and improve the spatial resolution of the NSMM image. The results of electromagnetic simulation and line scan measurement demonstrate the critical parameters affecting the sensitivity of NSMM, such as the length of the probe extending out of the cavity, the tip–sample distance, and the tip apex size. The tilt images can rotate successfully to the horizontal plane with the tilt correction methods, and the local average and re-interpolation are applied to denoise the images. Experimental NSMM images of copper thin film grid, coin texture, lithography mask, and leaf vein are obtained. The images before and after correction verify the improvement of the spatial resolution with all the above methods.

Tilt Correction Method of Pointer Meter Based on Deep Learning

Tilt Correction Method of Pointer Meter Based on Deep Learning

A Novel Tilt Correction Technique for Irradiance Sensors and Spectrometers On-Board Unmanned Aerial Vehicles

In unstable atmospheric conditions, using on-board irradiance sensors is one of the only robust methods to convert unmanned aerial vehicle (UAV)-based optical remote sensing data to reflectance factors. Normally, such sensors experience significant errors due to tilting of the UAV, if not installed on a stabilizing gimbal. Unfortunately, such gimbals of sufficient accuracy are heavy, cumbersome, and cannot be installed on all UAV platforms. In this paper, we present the FGI Aerial Image Reference System (FGI AIRS) developed at the Finnish Geospatial Research Institute (FGI) and a novel method for optical and mathematical tilt correction of the irradiance measurements. The FGI AIRS is a sensor unit for UAVs that provides the irradiance spectrum, Real Time Kinematic (RTK)/Post Processed Kinematic (PPK) GNSS position, and orientation for the attached cameras. The FGI AIRS processes the reference data in real time for each acquired image and can send it to an on-board or on-cloud processing unit. The novel correction method is based on three RGB photodiodes that are tilted 10° in opposite directions. These photodiodes sample the irradiance readings at different sensor tilts, from which reading of a virtual horizontal irradiance sensor is calculated. The FGI AIRS was tested, and the method was shown to allow on-board measurement of irradiance at an accuracy better than ±0.8% at UAV tilts up to 10° and ±1.2% at tilts up to 15°. In addition, the accuracy of FGI AIRS to produce reflectance-factor-calibrated aerial images was compared against the traditional methods. In the unstable weather conditions of the experiment, both the FGI AIRS and the on-ground spectrometer were able to produce radiometrically accurate and visually pleasing orthomosaics, while the reflectance reference panels and the on-board irradiance sensor without stabilization or tilt correction both failed to do so. The authors recommend the implementation of the proposed tilt correction method in all future UAV irradiance sensors if they are not to be installed on a gimbal.

Fast Cartoon-Texture Decomposition Filtering Based License Plate Detection Method

Vehicle license plate detection is an important step in automatic license plate recognition, which is prone to be influenced by the background interference and complex environment conditions. It is known that cartoon-texture decomposition split an image into geometric cartoon and texture component, which can remove background interference away from the vehicle image. In this paper, we introduce a fast cartoon-texture decomposition filter into the detection process. Combining the edge detection, morphological filtering and Radon transform based tilt correction method, we formulate a new license plate detection algorithm. Experiment results confirm that the proposed algorithm can remove background interference away, inhibit the emergence of fake license plates, and improve the detection accuracy. Moreover, there is no inner loop iteration in the new algorithm, so it is fast and high-efficiency.

A Horizontal Tilt Correction Method for Ship License Numbers Recognition

An automatic ship license numbers (SLNs) recognition system plays a significant role in intelligent waterway transportation systems since it can be used to identify ships by recognizing the characters in SLNs. Tilt occurs frequently in many SLNs because the monitors and the ships usually have great vertical or horizontal angles, which decreases the accuracy and robustness of a SLNs recognition system significantly. In this paper, we present a horizontal tilt correction method for SLNs. For an input tilt SLN image, the proposed method accomplishes the correction task through three main steps. First, a MSER-based characters’ center-points computation algorithm is designed to compute the accurate center-points of the characters contained in the input SLN image. Second, a L1- L2 distance-based straight line is fitted to the computed center-points using M-estimator algorithm. The tilt angle is estimated at this stage. Finally, based on the computed tilt angle, an affine transformation rotation is conducted to rotate and to correct the input SLN horizontally. At last, the proposed method is tested on 200 tilt SLN images, the proposed method is proved to be effective with a tilt correction rate of 80.5%.

A License Plate Tilt Correction Algorithm Based on the Character Median Line Algorithme de correction d’inclinaison de plaque d’immatriculation basé sur la ligne médiane du caractère

License plates intelligent identification systems must be able to correct the tilt of a license plate in an image. Aiming at improving on the low tilt accuracy, complex algorithms, and weak robustness against noise of existing tilt correction methods, we proposed an algorithm based on the character median line. The license plate image is first preprocessed, and a projection method is applied to find and segment the character region, resulting in a license plate with no border. For the no border license plate image, we then fix x-coordinates, and find the maximum and minimum values of y-coordinates, and put them into a matrix. The next step is to obtain the mean value of the maximum and minimum values of y, obtain the point sets on the character median line of the license plate, and remove the singular points using a threshold. Finally, a straight line is fitted using the least-squares method, and the tilt angle is obtained by applying a formula for the slope and the angle. For a tilted and damaged license plate, experiments show that the proposed algorithm is simple, has a low error ratio, and has good robustness against noise and deformation.

Effects of coordinate rotations on eddy fluxes over a forest on a mountainous terrain in Northeast China.

Coordinate rotation is an essential step in eddy covariance (EC) flux measurements particularly on complex terrains. Systematically assessing impacts of coordinate rotation methods can improve the accuracy in EC flux estimations. Taking the Maoershan flux tower in a temperate deci-duous forest on valley slopes as a case, we comprehensively examined the effects of various tilt-correction methods on sensible heat flux (H), latent heat flux (LE), CO2 fluxes (Fc), energy ba-lance, friction velocity (u*), and vertical velocity (w) using the standardized major axis method. Compared with the unrotated fluxes, the double rotation (DR), planar fit (PF), vertical velocity unbiased planar fit (NBPF), monthly planar fit (MPF), triple rotation (TR) and monthly sector-wist planar fit (MSWPF) changed the H by +1.5%, +3.8%, +3.1%, +3.3%, -1.3% and -7.1%, respectively. The NBPF and DR increased LE by 1.0% and 0.4%, respectively. The PF also increased LE by 0.671 W·m-2, and the MPF decreased LE by 0.4%, but increased the intercept by 0.747 W·m-2. In contrast, the MSWPF and TR decreased the LE by 4.5% and 15.1%, respectively. The coordinate rotation reduced the Fc by 6.0% (DR)-12.1% (TR). Among the studied methods, the PF increased the energy balance closure by about 2%, whereas the TR decreased it by about 6%. In the light of u* and w, the TR and NBPF were inappropriate for anemometer tilt correction. Considering the precision and practical application of EC measurements, we recommend the PF as the first choice for the Maoershan flux tower site, followed by the DR. These findings are useful for tilt correction of anemometer in EC flux observations over complex terrains.

A Retrospective, Iterative, Geometry-Based (RIGB) tilt-correction method for radiation observed by automatic weather stations on snow-covered surfaces: application to Greenland

Abstract. Surface melt and mass loss of the Greenland Ice Sheet may play crucial roles in global climate change due to their positive feedbacks and large fresh-water storage. With few other regular meteorological observations available in this extreme environment, measurements from automatic weather stations (AWS) are the primary data source for studying surface energy budgets, and for validating satellite observations and model simulations. Station tilt, due to irregular surface melt, compaction and glacier dynamics, causes considerable biases in the AWS shortwave radiation measurements. In this study, we identify tilt-induced biases in the climatology of surface shortwave radiative flux and albedo, and retrospectively correct these by iterative application of solar geometric principles. We found, over all the AWS from the Greenland Climate Network (GC-Net), the Kangerlussuaq transect (K-transect) and the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) networks, insolation on fewer than 40 % of clear days peaks within ±0.5 h of solar noon time, with the largest shift exceeding 3 h due to tilt. Hourly absolute biases in the magnitude of surface insolation can reach up to 200 W m−2, with respect to the well-understood clear-day insolation. We estimate the tilt angles and their directions based on the solar geometric relationship between the simulated insolation at a horizontal surface and the observed insolation by these tilted AWS under clear-sky conditions. Our adjustment reduces the root mean square error (RMSE) against references from both satellite observation and reanalysis by 16 W m−2 (24 %), and raises the correlation coefficients with them to above 0.95. Averaged over the whole Greenland Ice Sheet in the melt season, the adjustment in insolation to compensate station tilt is ∼ 11 W m−2, enough to melt 0.24 m of snow water equivalent. The adjusted diurnal cycles of albedo are smoother, with consistent semi-smiling patterns. The seasonal cycles and inter-annual variabilities of albedo agree better with previous studies. This tilt-corrected shortwave radiation data set derived using the Retrospective, Iterative, Geometry-Based (RIGB) method provide more accurate observations and validations for surface energy budgets studies on the Greenland Ice Sheet, including albedo variations, surface melt simulations and cloud radiative forcing estimates.

Automatic license plate detection in hazardous condition

Automatic detection of license plate (LP) is to localize a license plate region from an image without human involvement. So far a number of methods have been introduced for automatic license plate detection (ALPD), but most of them do not consider various hazardous image conditions that exist in many real driving situations. Hazardous image condition means an image can have rainy or foggy weather effects, low contrast environments, objects similar to LP in the background, and horizontally tilted LP area. All these issues create challenges in developing effective ALPD method. In this paper, we propose a new ALPD method which effectively detects LP area from an image in the hazardous conditions. For rain removal we apply a novel method that uses frequency domain mask to filter rain streaks from an image. A new contrast enhancement method with a statistical binarization approach is introduced in the proposed ALPD for handling low contrast indoor, night, blurry and foggy images. For correcting tilted LP, we apply Radon transform based tilt correction method for the first time. To filter non-LP regions, a new condition is used which is based on image entropy. We test the proposed ALPD method on 850 car images having different hazardous conditions, and achieve satisfactory results in LP detection.

Comparison of airborne gravity processing results by GravPRO and Newton software packages

Zero-length spring gravity sensors, such as the Micro-g LaCoste Turnkey Airborne Gravity System (TAGS), are widely used in airborne gravimetry applications due to their virtually drift-free characteristics. However, the quality of the final gravity product depends on the methods chosen to correct for several dynamic effects, including the Eötvös correction, the vertical acceleration correction of the moving aircraft, and the instrument platform tilt correction. For geodetic applications using regional gravity field mapping for geoid determination, the choices of correction method are extremely important because the flights are done uncommonly high and fast. For this reason, and in support of the Gravity for the Redefinition of the American Vertical Datum (GRAV-D) project, the National Oceanic and Atmospheric Administration’s National Geodetic Survey (NGS), and Fugro Geospatial have independently developed airborne gravity processing software packages for TAGS data — called Newton and GravPRO, respectively. We have evaluated the airborne gravity data processing methods that are used in the two software packages. We processed a GRAV-D data set collected by NGS over Louisiana and the Gulf of Mexico in 2008 with both packages, we compared the results for each major data correction applied, and we evaluated unique add-on features and tools. The results determined that the two software packages were very comparable, both yielding an excellent crossover root-mean-square of 1.8 mGal without any crossover adjustment applied. For the worst 14% of survey lines, which had higher levels of aircraft dynamics during flight, GravPRO was able to retain more data due to advantages in its platform tilt correction method. Also, GravPRO’s instrument calibration function, which is based on crossover error analysis, found a 45% improvement in achievable survey precision from approximately 2 mGal to approximately 1 mGal when comparing the test data set to a global gravity model.

Vehicle License Plate Detection and Tilt Correction Based on HSI Color Model and SUSAN Corner Detector

Detection and tilt correction of vehicle license plates are inevitable problems to be solved before developing Intelligent Transportation Systems. This paper describes a method of extraction of the vehicle license plate region from a vehicle image with tilt correction. The method consists of five distinct phases: segmenting color, labeling and filtering, correcting tilt, verifying candidate region, and segmenting license plate characters. Initially, an adaptive technique with labeling and filtering capability is utilized to select a statistical threshold value in the HSI color space for detecting candidate vehicle license plate regions. In this way the proposed method can overcome the limitation of the failure to detect a license plate when the vehicle body and license plate are similar colors. The slopes and tilt angles in both the horizontal and vertical directions of the skewed vehicle license plate are determined using the candidate corner points detected by the Smallest Univalue Segment Assimilating Nucleus corner detector, and the license plate region is rotated accordingly. Finally, a horizontal and vertical position histogram is employed to segment the candidate region into rows and constituent characters. The proposed tilt correction method is compared with the least square fitting with perpendicular offsets method and found to outperform results when the tilt angle gradually increases. 145 vehicle images were used for testing with different conditions and the results are presented to prove its efficiency and effectiveness.

Tilt correction algorithm based on aggregation of grating projection sequences

In view of the correction error problem which is caused by some factors such as dithering, the authors presented a new optical tilt correction method based on grating projection. The method was based on the analysis of each pixel of the data array in a sequence of fringe patterns having multiple frequencies, and setup model for pixel coordinates and pixelslope. Then skew angles of fringes were calculated by trigonometry with the relationship between tilt angle and pixel-slope. At last, tilt correction was realized. The experimental results show that, the algorithm is capable of accurately detecting angle within the range [- 90°,90°], accuracy is 99%. Compared with other algorithms such as Hough transform, the proposed algorithm improves precision and accuracy significantly.

Compression paddle tilt correction in full-field digital mammograms

During the acquisition of a mammogram the breast is compressed between the compression paddle and the support table. When compression is applied, the upper plate is tilted which results in variation in breast thickness from the chest wall to the breast margin. Variation in breast thickness influences the grey-level values of the image and hampers image analysis, such as volumetric breast density estimation. In this paper, we present and compare two methods that estimate and correct image tilt. The first method estimates tilt from fatty tissue regions. The second method is based on the entropy of the grey-level distribution of the image. Both methods use a classifier that distinguishes fatty areas from dense tissue based on texture features independent of tilt. The tilt correction methods are evaluated by assessing their accuracies in estimating artificial tilts that are added to images that are known to have only a small tilt. On average, both methods are able to estimate the artificial tilt. To the best of our knowledge, this is the first paper that presents and validates tilt correction methods on individual mammograms.

Quality Control and Tilt Correction Effects on the Turbulent Fluxes Observed at an Ocean Platform

AbstractThis study investigates atmospheric factors influencing the quality and the postprocessing (e.g., tilt correction) of fast-response measurements of turbulent fluxes for difficult open-sea measurements over an offshore platform. The data were collected at the Ieodo Ocean Research Station over the Yellow Sea during the period from 5 November 2007 to 19 February 2008. The quality control removal of the data generally depends on wind speed, relative humidity, significant wave height, visibility, and stability. The removal of substantial water vapor data with weak-wind stable conditions is investigated. Three different tilt correction algorithms (double rotation, triple rotation, and planar fit) are applied to correct the data because of inadvertent tilt of sonic anemometers. The choice of tilt correction method significantly influences the angle between the wind and stress direction.

TILT CORRECTION METHODS FOR CT AND MR MEDICAL IMAGES

In this paper, the tilt correction of computerized tomography (CT) and magnetic resonance (MR) medical images is the main point of interest. The centroid of the medical subimage is calculated, and the rotation angle α is obtained by separately using two methods: singular value decomposition (SVD) and principal component analysis (PCA), respectively. In addition, the whole medical image is rotated around the centroid by -α to correct the tilt. Based on this, according to the uniformity of the medical subimage the rotation angle α is further adjusted, which achieves better correction effect and performance. The experimental results show that the correction effect of SVD is the same as that of PCA, the proposed methods are fairly reliable and accurate for the determination of tilt angles, and are practical and effective tilt correction techniques. In addition, the correction methods are regarded as the preprocesses of image registration, and hence are used to get the registering parameters by incorporating the pattern search method. The experimental results reveal that they can significantly reduce the computational load, accurately get transformation parameters, and overcome the problem of easily getting into the local optimum.