Uniform Gray Scale Research Articles

Image encryption algorithm based on DNA mutation and a novel four-dimensional hyperchaos

Abstract Aiming at the problem that insufficient complexity of ordinary multi-dimensional chaotic systems and the cumbersome design of encryption algorithms without excellent encryption effects. This paper constructs a four-dimensional hyperchaotic system with high Lyapunov exponent and complex dynamic behavior. We designed an encryption algorithm based on point mutation, mutation diffusion, and folding mutation in DNA mutations. During the encryption process, we perform point mutation transformation on the entire base sequence, then spread the mutations one by one starting from the second base of the sequence, and finally flip every four base sequences according to folding mutations. The images encrypted by this algorithm have a uniform grayscale histogram, high information entropy, and high key sensitivity. It can resist exhaustive attacks, noise attacks, cropping attacks, and differential attacks, and have a fast encryption speed.

Infrared Bilateral Polarity Ship Detection in Complex Maritime Scenarios.

In complex maritime scenarios where the grayscale polarity of ships is unknown, existing infrared ship detection methods may struggle to accurately detect ships among significant interference. To address this issue, this paper first proposes an infrared image smoothing method composed of Grayscale Morphological Reconstruction (GMR) and a Relative Total Variation (RTV). Additionally, a detection method considering the grayscale uniformity of ships and integrating shape and spatiotemporal features is established for detecting bright and dark ships in complex maritime scenarios. Initially, the input infrared images undergo opening (closing)-based GMR to preserve dark (bright) blobs with the opposite suppressed, followed by smoothing the image with the relative total variation model to reduce clutter and enhance the contrast of the ship. Subsequently, Maximally Stable Extremal Regions (MSER) are extracted from the smoothed image as candidate targets, and the results from the bright and dark channels are merged. Shape features are then utilized to eliminate clutter interference, yielding single-frame detection results. Finally, leveraging the stability of ships and the fluctuation of clutter, true targets are preserved through a multi-frame matching strategy. Experimental results demonstrate that the proposed method outperforms ITDBE, MRMF, and TFMSER in seven image sequences, achieving accurate and effective detection of both bright and dark polarity ship targets.

Research on the design of automatic image processing function for intelligent face management system

Abstract Around the background of rapid development of intelligent technology, an efficient image processing system oriented to the smart management of human faces is focused on. The system is mainly developed towards high speed, high definition, high integration and reliability. The article investigates a novel automatic image processing algorithm, covering three key modules: automatic exposure control, color interpolation and chromaticity space conversion. The algorithm can process the output image of CMOS sensor in Bayer format in real time and adjust the image parameters to obtain a high-quality image. In terms of face recognition performance, the algorithm has a significant advantage in recognition speed compared with other algorithms, and the average recognition accuracy reaches 94.258%. In the practical application of ID card portrait processing, the image shows a more uniform grayscale distribution in the range of 5 to 255 after automatic color adjustment, and the color quality is significantly improved. Meanwhile, in the portrait enhancement experiments, the images obtained with this image automatic processing algorithm outperform the traditional ID card image processing methods regarding information entropy, mutual information, standard deviation and peak signal-to-noise ratio (PSNR).

Accurate measurement of high-reflective surface based on adaptive fringe projection technique

Fringe projection profilometry (FPP) is one of the most effective methods to obtain three-dimensional surface topography information about an object. However, for objects with large variations in surface reflectance, it is difficult to measure the saturated regions with conventional FPP. In this paper, a new adaptive fringe projection (AFP) method is proposed to solve this problem. Compared with existing methods, the proposed method can automatically generate low-intensity projected fringe patterns instead of requiring manual adjustment. First, we built a projection intensity model for the captured pixels and defined the surface reflection factor and environmental factor for saturated pixels. Then, a small number of uniform grayscale pattern sequences were projected to mark the saturated areas, while the surface reflection factor and the environment factor of individual pixels were calculated and a surface coefficient look-up table (SCLUT) was created. The low-intensity projected fringe patterns were automatically calculated and generated based on the captured uniform grayscale sequences of images to establish the mapping relationship between the camera image plane and the projector image plane. Finally, the optimal projection intensities of pixels in the saturated regions were calculated according to the SCLUT, and adaptive fringe patterns were generated. Experiments show that using the adaptive fringe patterns generated by the proposed method to measure objects can accurately adjust the projection intensity and substantially improve the measurement accuracy of high-reflective surface.

Three-dimensional measurement for specular reflection object based on adaptive fringe projection and phase measuring profilometry

ObjectiveUsing phase measuring profilometry (PMP) to measure the object with specular reflections is a very challenging task, a large deviation between the measured result and the actual data is caused by the highlights of the measured object surface. Therefore, a 3D measurement method for the object with a specular reflection based on adaptive fringe pattern projection (AFPP) is proposed in this paper. MethodsFirstly, a set of uniform grayscale images are projected to the measured object by a DLP projector. The gray level gradually decreases from 255 and stops when the number of saturated pixels in the camera image reaches 0. The masks of saturated pixels at each gray level are obtained. Secondly, the masks corresponding to two adjacent gray levels are compared respectively, and the optimal projection intensity of the camera image is obtained. Thirdly, the coordinates of the highlight pixels in the camera image are mapped to the projector image coordinate system, and the new fringe images are generated using the optimal projection intensity. Fourthly, the new fringe images are projected onto the measured object for 3D measurement. ResultsThe measurement experiments were implemented on the measured objects made of metal, plastic, and ceramic, respectively. Experiment results show that the proposed method can reduce the measurement deviation caused by the highlights and make the 3D reconstruction model more complete without additional cameras and hardware.

Predicting the Porosity in Selective Laser Melting Parts Using Hybrid Regression Convolutional Neural Network

Assessing the porosity in Selective Laser Melting (SLM) parts is a challenging issue, and the drawback of using the existing gray value analysis method to assess the porosity is the difficulty and subjectivity in selecting a uniform grayscale threshold to convert a single slice to binary image to highlight the porosity. This paper proposes a new approach based on the use of a Regression Convolutional Neural Network (RCNN) algorithm to predict the percent of porosity in CT scans of finished SLM parts, without the need for subjective difficult thresholding determination to convert a single slice to a binary image. In order to test the algorithm, as the training of the RCNN would require a large amount of experimental data, this paper proposed a new efficient approach of creating artificial porosity images mimicking the real CT scan slices of the finished SLM part with a similarity index of 0.9976. Applying RCNN improved porosity prediction accuracy from 68.60% for image binarization method to 75.50% using the RCNN. The algorithm was then further developed by optimizing its parameters using Bees Algorithm (BA), which is known to mimic the behavior of honeybees, and the hybrid Bees Regression Convolutional Neural Network (BA-RCNN) produced better prediction accuracy with a value of 85.33%.

Multi-temporal Cloud Pixels Reconstruction Method for Optical Remote Sensing Satellite Images

Bachground: The existence of cloud pixels reduces the practicability of optical satellite remote sensing data. Existing problems: Existing cloud reconstruction methods generally cannot solve the following problems:(1)Large-scale thick cloud cannot be well reconstructed. (2)There are high requirements for reconstructed data. (3)Most data used to reconstructed are single temporal images. Ways: In order to overcome these problems, a new multi temporal weighted aggregation method is proposed. Specifically, we adopt a multi-temporal iterative aggregation method for cloud pixels to reconstruct and a multi-temporal weighted aggregation method for cloud shadow pixels to reconstruct. Result: Finally, the experiment proves that our method can quickly and accurately complete the cloud reconstruction, and under the effective uniform color strategy, a cloud- free image with accurate geometric position and uniform gray scale can be obtained. Conclusion: Experiments prove that the pixel reconstruction method proposed in this paper has achieved good cloud and cloud shadow pixel reconstruction effects in different types of ground objects.

An effective and flexible method for improving the full grayscale uniformity of mini‐LED display

AbstractAs a new display technology, mini‐LED has more and more broad prospects. However, there are some difficult problems associated with mass transfer, yield, uniformity of brightness, and chroma. In order to improve the uniformity, especially in case of the low grayscale, we propose a fine full grayscale correction method, which includes precise pixel‐by‐pixel brightness and chroma extraction algorithm and level‐by‐level full grayscale correction algorithm. To ensure the uniformity inside the cabinet and between the cabinets, a full‐color viewing angle compensation and an adaptive cabinet seam correction algorithm are also proposed to achieve the arbitrary splicing of the cabinets.

Improved optical camera communication systems using a freeform lens.

Optical camera communication (OCC) systems, which utilize image sensors embedded in commercial-off-the-shelf devices to detect time and spatial variations in light intensity for enabling data communications, have stirred up researchers' interest. Compared to a direct OCC system whose maximum data rate is strongly determined by the LED source size, a reflected OCC system can break that limitation since the camera captures the light rays reflecting off an observation plane (e.g., a wall) instead of those light rays directly emanated from the light source. However, the low signal-to-noise ratio caused by the non-uniform irradiance distribution produced by LED luminaire on the observation plane in current reflected OCC systems cannot be avoided, hence low complexity and accurate demodulation are hard to achieve. In this paper, we present a FreeOCC system, which employs a dedicatedly tailored freeform lens to precisely control the propagation of modulated light. A desired uniform rectangular illumination is produced on the observation plane by the freeform lens, yielding a uniform grayscale distribution within the received frame captured by the camera in the proposed FreeOCC system. Then, the received signal can be easily demodulated with high accuracy by a simple thresholding scheme. A prototype of the FreeOCC system demonstrates the high performance of the proposed system, and two pulse amplitude modulation schemes (4-order and 8-order) are performed. By using the freeform lens, the packet reception rate is increased by 35% and 32%, respectively; the bit error rate is decreased by 72% and 59%, respectively, at a transmission frequency of 5 kHz. The results clearly show that the FreeOCC system outperforms the common reflected OCC system.

25.3: A Fine Correction Method for Improving the Full Grayscale Uniformity of Mini‐LED Display

As a new display technology, Mini‐LED has more and more broad prospects. However, there are some difficult problems, such as Mass Transfer, yield, Uniformity of brightness and chroma. In order to improve the uniformity, especially the low grayscale, we propose a fine full grayscale correction method, which includes precise pixel‐by‐pixel brightness and chroma extraction algorithm and level‐by‐level full grayscale correction algorithm. To ensure the uniformity of the interior of the cabinet and between the cabinets, the full‐color viewing angle compensation and adaptive cabinet edge seam correction algorithm is also proposed, which can realize the arbitrary splicing of the cabinets.

Secure multilevel permutation-diffusion based image encryption using chaotic and hyper-chaotic maps

This paper proposes a technique that encrypt images using chaotic and hyper-chaotic maps. To attain a high level of security and to get a better encryption effect, the proposed technique performs multilevel permutation and diffusion operations such as block, pixel, and bit-level to encrypt images. In this technique, block-level permutation operation is first performed using Alpar’s map followed by Arnold cat map based pixel-level permutations. Finally, in the permutation stage, hyper-chaotic map based bit-level shuffling operation is performed for over strengthening of the encryption system. To make the ciphertext totally independent of the plaintext, the proposed scheme performs all the three levels of diffusion operations such as bit, pixel, and block-level. In the diffusion stage, Piece-wise Linear Chaotic Map (PWLCM) based bit-level diffusion operation is first performed followed by pixel-level diffusion operation. Finally, block-level diffusion operation is performed to get encryption output. In each of the levels of encryption operation, a hash value (256-bits) of plaintext is used to strongly resist the algorithm against known-plaintext attack and chosen-plaintext attack. The security analyses and computer simulations indicate the good encryption outputs, higher key space and gray scale uniformity, stronger resistance of entropy, differential, and statistical attacks as well as fewer computations to perform encryption operation. This proves the strong ability of the proposed scheme to encrypt gray scale images.

Modulation transfer function measurement of the rigid endoscope by a random method

A random method is presented to measure the modulation transfer function (MTF) of the rigid endoscope, evaluating its imaging quality. The experimental setup includes a four-dimensional (4D) mobile platform, a non-full-screen liquid-crystal display (LCD), three different kinds of patterns, a nasoendoscope of 0° direction of view under measurement, a complementary metal oxide semiconductor (CMOS) device, and a computer. The method is divided into three steps to complete the MTF measurement. First the geometric distortion is evaluated to determine the suitable sampling matrix (SSM) by the grid pattern. Then the illuminance inhomogeneity distribution is evaluated to obtain the illuminance compensation curve by the uniform grayscale pattern. Finally the MTFs are acquired by analyzing the spatial frequency contents of the compensated SSMs by the random patterns. By analysis and comparison, the method can improve the stability and accuracy for the MTF measurement in a simplified way.

Region based five-axis tool path generation for freeform surface machining via image representation

Abstract This paper inaugurates a brand new five-axis tool path generation method for freeform surface machining, which is solely based on digital image processing. By utilizing image representation, a freeform surface can be digitized into a uniform grayscale image. With this novel representation, we come up with a region based five-axis tool path scheme with remarkably enhanced utility towards freeform surface machining process. The image representation possesses sufficient geometric data for us to evaluate the surface normal distribution and split the surface area accordingly via image processing algorithms. Since each partitioned region contains a limited surface inclination range, one rotary axis is locked with a certain angle during the processing of this region. In addition, by further exploiting the potential of the image representation, the cutter contact (CC) curves are extracted purely from the image of each partitioned region. Preliminary results show that this method is more than adequate for the tool path computation. The computed tool path outperforms the benchmarks by reducing the machining time for as much as 40%, as verified in the physical cutting test.

Intuitive Assessment of Mortality Based on Facial Characteristics: Behavioral, Electrocortical, and Machine Learning Analyses

Studies of various characteristics of the human face indicate that it contains a wealth of information about health status. Most studies involve objective measurement of facial features as correlated with historical health information. But some individuals also claim to be adept at intuitively gauging mortality based solely upon a quick glance at a person's photograph. To test this claim, we invited 12 such individuals to see if they could tell if a person was alive or dead based solely on a brief examination of his or her photograph. All photos used in the experiment were transformed into a uniform gray scale and counterbalanced across eight categories as follows: gender, age, gaze direction, glasses, head position, smile, hair color, and image resolution. Participants examined 404 photographs displayed on a computer monitor, one photo at a time, each shown for a maximum of 8seconds. Half of the individuals in the photos were deceased, and half were alive at the time the experiment was conducted. Participants were asked to indicate if they thought the person in a photo was living or deceased by pressing an appropriate button. Overall, mean accuracy on this task was 53.6%, where 50% was expected by chance (P = .005, two tail). Statistically significant accuracy was independently obtained in 5 of the 12 participants. We also collected 32-channel electrocortical recordings and observed a robust difference between images of deceased individuals correctly vs. incorrectly classified in the early event related potential at 100ms post-stimulus onset. We then applied machine learning techniques to classify the photographs based on 11 image characteristics; both random forest and logistic regression machine learning approaches were used, and both classifiers failed to achieve accuracy above chance level. Our results suggest that some individuals can intuitively assess mortality based on some as-yet unknown features of the face.

Prediction of Mortality Based on Facial Characteristics.

Recent studies have shown that characteristics of the face contain a wealth of information about health, age and chronic clinical conditions. Such studies involve objective measurement of facial features correlated with historical health information. But some individuals also claim to be adept at gauging mortality based on a glance at a person’s photograph. To test this claim, we invited 12 such individuals to see if they could determine if a person was alive or dead based solely on a brief examination of facial photographs. All photos used in the experiment were transformed into a uniform gray scale and then counterbalanced across eight categories: gender, age, gaze direction, glasses, head position, smile, hair color, and image resolution. Participants examined 404 photographs displayed on a computer monitor, one photo at a time, each shown for a maximum of 8 s. Half of the individuals in the photos were deceased, and half were alive at the time the experiment was conducted. Participants were asked to press a button if they thought the person in a photo was living or deceased. Overall mean accuracy on this task was 53.8%, where 50% was expected by chance (p < 0.004, two-tail). Statistically significant accuracy was independently obtained in 5 of the 12 participants. We also collected 32-channel electrophysiological recordings and observed a robust difference between images of deceased individuals correctly vs. incorrectly classified in the early event related potential (ERP) at 100 ms post-stimulus onset. Our results support claims of individuals who report that some as-yet unknown features of the face predict mortality. The results are also compatible with claims about clairvoyance warrants further investigation.

Application of An Improved Canny Algorithms Operator in RS Data

When we deploy the seismic line, the data received by seismometer will be affected by ground water bodies. Therefore, we need to extract water bodies by remote sensing image before deploy the seismic line. In this paper, an approach is proposed to extract water bodies. First, use Canny edge detector to extract the edges of the image. Second, based on three features of water body: gray-scale uniformity, edge irregularity and closed regions, this paper uses three means: dual-threshold judgment by gray-scale uniformity, edge irregularity verification based on least square method and closed region verification. During the extraction of water bodies in mountain regions which the topography was complicated, this approach proved to be fairly effective. And the deployment of seismic line was facilitated by this approach.

P‐123: A Method to Achieve Uniform Gray Scale to Gray Scale Response Times in LCDs

AbstractUniform gray scale to gray scale response times is achieved in liquid crystal displays for a large number of gray shades with wavelets based addressing technique. The method is demonstrated for 64 gray shades and it can be extended to other addressing techniques.

Neural Network Based Thickness Estimation from Multiple Radiographic Images

Back propagation (BP) type artificial neural networks (ANN) have been trained and used for thickness estimations from radiographic images. Test objects have been assembled from different materials and radiographic images of the test objects were obtained for thickness estimations. While some of the study has been based on the synthetic images formed through the radiographic simulation program XRSIM, the rest of the study has used actual radiographic images. The average estimation errors were 7% and 9% when two and three synthetic radiographic images obtained at different x-ray tube settings were used. With the actual images, the thickness of only one of the materials has been estimated and the material was identified. This has been due to the fact that scattering of x-rays by the test object results in a non uniform gray scale variation in the radiographic images even though the object thickness is uniform.

TH-C-I-609-08: Ultrasound Transducer Performance Evaluation With An Electronic Probe Tester

Purpose: Ultrasound transducer performance plays a major role in the integrity of B-mode mages and in image quality. A frequent problem with arrays is “element drop out,” caused by electronic or mechanical interruption of signals. Currently this is detected using visual inspection of images of patients and or phantoms. Our objectives were to evaluate an electronic probe tester for determining functionality of array transducers and to compare results of the tester with subjective analysis of images of uniform phantoms. Method and Materials: A FirstCall 2000 (Sonora Medical Systems) electronic transducer tester was used on array transducers. The device exercises each element in the array, measuring its capacitance, pulse-echo sensitivity, pulse width, center frequency and bandwidth using planar targets. Probe adapters and software enable the FirstCall to utilize connection configurations of different transducer manufacturers. Probes from Siemens Sequoia and Philips HDI 5000 machines available in the UW Hospital were tested. Images of a uniform phantom were obtained from each transducer using sensitivity and gain settings for uniform gray scale. The images were examined for evidence of element dropout. Results: Of twenty-one probes initially tested, nine exhibited some level of malfunction (>2 “dead” elements). Of the nine, four exhibited a significant level of malfunction (>5 dead elements). Probes that had only a few dead elements showed no signs of image degradation in the phantom tests. When multiple (∼5 or more) elements are dead, manifestations of the problem appeared in the phantom images. Conclusion: The FirstCall provides an objective test of transducer performance, with greater sensitivity than a phantom test. The penalty for using a probe with only a few dead elements may seem minimal if no indication is seen in a uniform phantom image. A clinically applicable threshold for determining whether a transducer is suitable for use still needs to be established.

Reliable Polymer-Stabilized Ferroelectric Liquid Crystal Device Using Thin Plastic Substrates

We developed a rollable polymer-stabilized ferroelectric liquid crystal (FLC) display device using thin plastic substrates. In a device using 200-μm-thick substrates which are fastened by polymer walls and networks made by photopolymerization-induced phase separation, disorder of the FLC alignment was caused by exfoliation of these walls in curvature radii of under 30 mm. Otherwise, the uniformity of the FLC alignment was maintained even after a device using 100-μm-thick substrates was bent at a radius of 7 mm. The enhanced bending tolerance does not depend on the FLC alignment direction, and the device could be bent both convexly and concavely without any FLC alignment change. A rollable device with a size of 100 × 100 mm exhibited uniform grayscale display operation between crossed polarizers when bent with a radius of 15 mm.