A 64-Step Gray Scale Driver Chip for a 132×64-Pixel Passive Matrix OLED

A mixed-signal driver chip for a 132 × 64-pixel passive matrix OLED panel is presented. The chip has a 64-step gray scale control using the PWM method and two-step voltage pre-charge technology to pre-charge the OLED pixels. It consists of a digital controller,SRAM for display data memory,a DC-DC voltage converter,reference current generators,a pre-charge voltage generator,64 common drivers, and 132 segment drivers. The single chip is a typical current-drive circuit. It has been implemented in a Chartered 0.35/μm 18V HV （DDD） CMOS process with a die area of 10mm× 2mm. Test results show that the power consumption of the whole chip and all pixels with a constant driving current of 100μA while displaying the highest gray scale is 294mW with a 12V high voltage supply and a 3V low voltage supply.

Design on AM-OLED display control ASIC with high gray scale levels

The paper puts forward a method on controlling the AM-OLED panel to display image with high gray scale levels. It also gives an ASIC design sample to implement this method. A twenty sub-fields scan scheme has been taken into use in the chip to display 256 gray scale levels on a QVGA resolution AM-OLED display screen. The functions of image scaling and rotating have also been implemented for multiply application. The simulation and chip test result show that the chip design has met the design requirements.

Searching high gray scale FPD scanning matrix based on PSO

With the increase of gray scale and flat panel display （FPD） size, subspace bitwise scanning strategy can be replaced traditional scanning method to cut down frame frequency. However, the direct searching strategy （DSS） becomes unfeasible to obtain corresponding high gray scale scanning matrix. Thus, particle swarm optimization （PSO） is introduced to accelerate searching for high gray scale weights scanning matrix （WSM） with its parallelism and global optimization feature. Finally a WSM of 256 gray scales is found out successfully with Matlab, which both gray linearity and scanning efficiency are satisfied.

Assessing Gray Scale Grades for Color Change of Dyed Fabrics via Image Processing Technology

Gray scale grades for color change of dyed fabrics are assessed via image processing technology.Digital images of groups of specimens are obtained,cropped,and saved as JPEG format.Relationships between gray scale grades for color change and the corresponding color differences calculated via image processing technology are investigated,compared with those obtained from high accurate computer color matching system.Results show that the new method is acceptable with an accuracy of 92.0% when the grading errors are of not more than one grade.

Diagnostic Accuracy of Gray Scale Sonography for the Detection of Malignant Breast Tumour

Background: Gray scale sonography is an important diagnostic tool for the detection of malignant breast tumour. Objective: The purpose of the present study was to find out the diagnostic validity gray scale sonography to detect malignant lesions of breast. Methodology: This cross-sectional study was carried out in the department of Radiology and Imaging, in collaboration with the department of Surgery and Pathology at Banghabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, from July 2008 to June 2009 for a period of one year. Women presented with clinically suspected breast mass from outpatients’ department (OPD) or inpatient department (IPD) were purposively selected and was Ultrasonographic diagnosis. 2-D Real-Time B-Mode Ultrasonographic examinations were done using high frequency (7.5 MHz) linear transducer. Result: Test of validity was done for color Doppler Sonographic findings in evaluation of benign and malignant breast lesion. Out of 50 cases, 23 cases were true positive;4 cases were false negative;1 case was false positive;22 cases were true negative confirmed by histopathology. Here sensitivity and specificity of Gray scale ultrasonography were 85.18% and 95.0% respectively. Here accuracy of Gray scale study was 90.0%. Positive predictive value was 95.83% and negative predictive value was 84.61%. Conclusion: Gray scale ultrasonography is a useful method in the differentiation between benign and malignant breast masses.

Electroluminescence Gray Scale Display Driving Method and Circuit

The increasing use of color terminals for personal computers has raised a demand for video graphic adapter(VGA)-format panel displays. Since only monochrome(ZnS∶Mn) electroluminescence(EL) displays of suitable size and speed are available, lack of colors has to be replaced by grayscale in the first place. There are two basic driving methods to achieve grayscale in thin-film EL displays: pulse amplitude modulation(PAM) method and pulse width modulation(PWM) method. But there are serious disadvantages of the two traditional methods. For the former method, the high voltage PAM ICs are too expensive to produce the grayscale EL display in bulks and the driver integrated circuit(IC) is complex. Though the PWM method has good grayscale display quality, the hardware implementation is too complex. A new driving method with which the width and the amplitude of the pulse can be modulated and simultaneously the challenge can be solved efficaciously is presented.

A Secure Robust Gray Scale Image Steganography Using Image Segmentation

Steganography is the art of hiding a secret message in some kind of media. The main goal is not to hide only the secret message but also the existence of communication and secure data transferring. There are a lot of methods that were utilized for building the steganography;such as LSB (Least Significant Bits), Discrete Cosine Transform (DCT), Discrete Fourier Transform, Spread-Spectrum Encoding, and Perceptual Masking, but all of them are challenged by steganalysis. This paper proposes a new technique for Gray Scale Image Steganography that uses the idea of image segmentation and LSB to deal with such problem. The proposed method deals with different types of images by converting them to a virtual gray scale 24 bitmaps, finds out the possible segments inside image and then computes the possible areas for each segment with boundaries. Any intruder trying to find the transformed image will not be able to understand it without the correct knowledge about the transformation process. The knowledge is represented by the key of image segmentation, key of data distribution inside segment (area selection), key of mapping within each area segment, key agreement of cryptography method, key of secret message length and key of message extension. Our method is distinguishing oneself by one master key to generate the area selection key, pixels selection keys and cryptography key. Thus, the existence of secret message is hard to be detected by the steganalysis. Experiment results show that the proposed technique satisfied the main requirements of steganography;visual appearance, modification rate, capacity, undetectability, and robustness against extraction (security). Also it achieved the maximum capacity of cover image with a modification rate equals 0.04 and visual quality for stego-image comparable to cover image.

New seismic attribute:Fractal scaling exponent based on gray detrended fluctuation analysis

Seismic attributes have been widely used in oil and gas exploration and development. However, owing to the complexity of seismic wave propagation in subsurface media, the limitations of the seismic data acquisition system, and noise interference, seismic attributes for seismic data interpretation have uncertainties. Especially, the antinoise ability of seismic attributes directly affects the reliability of seismic interpretations. Gray system theory is used in time series to minimize data randomness and increase data regularity. Detrended fluctuation analysis （DFA） can effectively reduce extrinsic data tendencies. In this study, by combining gray system theory and DFA, we propose a new method called gray detrended fluctuation analysis （GDFA） for calculating the fractal scaling exponent. We consider nonlinear time series generated by the Weierstrass function and add random noise to actual seismic data. Moreover, we discuss the antinoise ability of the fractal scaling exponent based on GDFA. The results suggest that the fractal scaling exponent calculated using the proposed method has good antinoise ability. We apply the proposed method to 3D poststack migration seismic data from southern China and compare fractal scaling exponents calculated using DFA and GDFA. The results suggest that the use of the GDFA-calculated fractal scaling exponent as a seismic attribute can match the known distribution of sedimentary facies.

On Fault Diagnosis of Rotating Machinery Using Wavelet Time-division Scale Level Moment

Based on an in-depth study of wavelet gray moment, we proposed a concept of a time-division scale level moment and gave the specific definition; ulteriorly, we discussed the factors which affected the fault diagnosis ability of a time-division scale level moment. The analysis results in the caculation of six typical fault signals show that the time-division scale level moment can be used to display the detailed information of a wavelet gray level image, extract the signal＇s characteristics effectively, and distinguish the vibration fault. Compared to the method of a wave gray moment vector, the method mentioned in this paper can provide higher calculation speed and higher capacity of fault identification, so it is more suitable for online fault diagnosis for rotating machinery.

Anti-Robinson Structures for Analyzing Three-Way Two-Mode Proximity Data

Multiple discrete (non-spatial) and continuous (spatial) structures can be fitted to a proximity matrix to increase the information extracted about the relations among the row and column objects vis-à-vis a representation featuring only a single structure. However, using multiple discrete and continuous structures often leads to ambiguous results that make it difficult to determine the most faithful representation of the proximity matrix in question. We propose to resolve this dilemma by using a nonmetric analogue of spectral matrix decomposition, namely, the decomposition of the proximity matrix into a sum of equally-sized matrices, restricted only to display an order-constrained patterning, the anti-Robinson (AR) form. Each AR matrix captures a unique amount of the total variability of the original data. As our ultimate goal, we seek to extract a small number of matrices in AR form such that their sum allows for a parsimonious, but faithful reconstruction of the total variability among the original proximity entries. Subsequently, the AR matrices are treated as separate proximity matrices. Their specific patterning lends them immediately to the representation by a single (discrete non-spatial) ultrametric cluster dendrogram and a single (continuous spatial) unidimensional scale. Because both models refer to the same data base and involve the same number of parameters, estimated through least-squares, a direct comparison of their differential fit is legitimate. Thus, one can readily determine whether the amount of variability associated which each AR matrix is most faithfully represented by a discrete or a continuous structure, and which model provides in sum the most appropriate representation of the original proximity matrix. We propose an extension of the order-constrained anti-Robinson decomposition of square-symmetric proximity matrices to the analysis of individual differences of three-way data, with the third way representing individual data sources. An application to judgments of schematic face stimuli illustrates the method.

Non-iterative image feature matching algorithm based on reference point correspondences

Based on the coded and non-coded targets, the targets are extracted from the images according to their size, shape and intensity etc., and thus an improved method to identify the unique identity（D） of every coded target is put forward and the non-coded and coded targets are classified. Moreover, the gray scale centroid algorithm is applied to obtain the subpixel location of both uncoded and coded targets. The initial matching of the uncoded target correspondences between an image pair is established according to similarity and compatibility, which are based on the ID correspondences of the coded targets. The outliers in the initial matching of the uncoded target are eliminated according to three rules to finally obtain the uncoded target correspondences. Practical examples show that the algorithm is rapid, robust and is of high precision and matching ratio.

Dynamic infrared scene simulation using grayscale modulation of digital micro-mirror device

Dynamic infrared scene simulation is for discovering and solving the problems encountered in designing, developing and manufacturing infrared imaging guidance weapons. The infrared scene simulation is explored by using the digital grayscale modulation method. The infrared image modulation model of a digital micro-mirror device （DMD） is established and then the infrared scene simulator prototype which is based on DMD grayscale modulation is developed. To evaluate its main parameters such as resolution, contrast, minimum temperature difference, gray scale, various DMD subsystems such as signal decoding, image normalization, synchronization drive, pulse width modulation （PWM） and DMD chips are designed. The infrared scene simulator is tested on a certain infrared missile seeker. The test results show preliminarily that the infrared scene simulator has high gray scale, small geometrical distortion and highly resolvable imaging resolution and contrast and yields high-fidelity images, thus being able to meet the requirements for the infrared scene simulation inside a laboratory.

Design of a 16 gray scales 320×240 pixels OLED-on-silicon driving circuit

A 320×240 pixel organic-light-emitfing-diode-on-silicon （OLEDoS） driving circuit is implemented using the standard 0.5μm CMOS process of CSMC. It gives 16 gray scales with integrated 4 bit D/A converters. A three- transistor voltage-programmed OLED pixel driver is proposed, which can realize the very small current driving required for the OLEDoS microdisplay. Both the D/A converter and the pixel driver are implemented with pMOS devices. The pass-transistor and capacitance in the OLED pixel driver can be used to sample the output of the D/A converter. An additional pMOS is added to OLED pixel driver, which is used to control the D/A converter operating only when one row is on. This can reduce the circuit＇s power consumption. This driving circuit can work properly in a frame frequency of 50 Hz, and the final layout of this circuit is given. The pixel area is 28.4 × 28.4μm^2 and the display area is 10.7 × 8.0 mm^2 （the diagonal is about 13 mm）. The measured pixel gray scale voltage shows that the function of the driver circuit is correct, and the power consumption of the chip is about 350 mW.

Outdoor relative radiometric calibration method using gray scale targets

The radiometric calibration of remote sensors is a basis and prerequisite of information quantification in remote sensing. This paper proposes a method for outdoor relative radiometric calibration using gray scale targets. In this method, the idea of two substitutions is adopted. Sunlight is used to replace the integrating sphere light source, and gray scale targets are used to re-place the diffuser. In this way, images at different radiance levels obtained outdoors can calculate the relative radiometric cali-bration coefficients using the least square method. The characteristics of this method are as follows. Firstly, compared with la-boratory calibration, it greatly reduces the complexity of the calibration method and the test cost. Secondly, compared with the existing outdoor relative radiometric calibration of a single radiance level, it uses test images of different radiance levels to re-duce errors. Thirdly, it is easy to operate with fewer environmental requirements, has obvious advantages in the rapid calibra-tion of airborne remote sensors before or after flight and is practical in engineering. This paper theoretically and experimental-ly proves the feasibility of this method. Calibration experiments were conducted on the wide-view multispectral imager (WVMI) using this method, and the precision of this method was evaluated by analyzing the corrected images of large uniform targets on ground. The experiment results have demonstrated that the new method is effective and its precision meets the re-quirement of the absolute radiometric calibration.

Pulsed arterial spin labeling effectively and dynamically observes changes in cerebral blood flow after mild traumatic brain injury

Cerebral blood flow is strongly associated with brain function, and is the main symptom and diagnostic basis for a variety of encephalopathies. However, changes in cerebral blood flow after mild traumatic brain injury remain poorly understood. This study sought to observe changes in cerebral blood flow in different regions after mild traumatic brain injury using pulsed arterial spin labeling. Our results demonstrate maximal cerebral blood flow in gray matter and minimal in the white matter of patients with mild traumatic brain injury. At the acute and subacute stages, cerebral blood flow was reduced in the occipital lobe, parietal lobe, central region, subcutaneous region, and frontal lobe. Cerebral blood flow was restored at the chronic stage. At the acute, subacute, and chronic stages, changes in cerebral blood flow were not apparent in the insula. Cerebral blood flow in the temporal lobe and limbic lobe diminished at the acute and subacute stages, but was restored at the chronic stage. These findings suggest that pulsed arterial spin labeling can precisely measure cerebral blood flow in various brain regions, and may play a reference role in evaluating a patient＇s condition and judging prognosis after traumatic brain injury.

A new experimental study on noninvasive thermometry in HIFU

The measurement of temperature at the heated point is very important and difficult for the treatment of tumor using HIFU(High intensity focused ultrasound). According to the theory that the gray scale value varies with the ultrasound transmitting through different tissues at different temperatures, a set of experiment equipment was designed to describe the temperature field in tissues by using the characteristics of the ultrasonic image, and an experiment was carried out with fresh liver and muscle tissues of pigs in a temperature arrange of 26 ℃ to 64 ℃. The statistical curve of the experiment demonstrates: (1) The gray scales vary in accordance with the changes in the temperature of tissue and it is feasible to measure the temperature at the heated point by making use of the gray scale variations;(2) Non linearity is the characteristics of temperature changes and the gray scale of tissues at different temperature phases. Moreover, the gray scale varies from up to down phase at the same temperature phase;(3)The gray scale for the same temperature range varies with different tissues. An experimented formula is proposed for the measurement of fresh liver and muscle tissues of pigs.

Regional brain structural abnormality in ischemic stroke patients:a voxel-based morphometry study

Our previous study used regional homogeneity analysis and found that activity in some brain areas of patients with ischemic stroke changed significantly. In the current study, we examined structural changes in these brain regions by taking structural magnetic resonance imaging scans of 11 ischemic stroke patients and 15 healthy participants, and analyzing the data using voxel-based morphometry. Compared with healthy participants, patients exhibited higher gray matter density in the left inferior occipital gyrus and right anterior white matter tract. In contrast, gray matter density in the right cerebellum, left precentral gyrus, right middle frontal gyrus, and left middle temporal gyrus was less in ischemic stroke patients. The changes of gray matter density in the middle frontal gyrus were negatively associated with the clin- ical rating scales of the Fugl-Meyer Motor Assessment （r = -0.609, P = 0.047） and the left middle temporal gyrus was negatively correlated with the clinical rating scales of the nervous functional deficiency scale （r = -0.737, P = 0.010）. Our findings call objectively identify the functional abnormality in some brain regions of ischemic stroke patients.

基于区间灰度的区域物流配送中心选址实证分析

结合区域物流配送中心选址评价中存在的不确定性和评价信息量获取不充足性,提出采用语言标度和灰度构成的有序对作为评价标度,并利用OWA算子获得评价指标权重和组合权重,给出一种区域物流配送中心选址方法,最后实证分析了该方法的可行性和科学性。

Magnetic Tile Surface Defect Detection Based on Texture Feature Clustering

In the field of magnetic tile surface detection, artificial detection efficiency is low, and the traditional image segmentation algorithm cannot show good performance when the gray scale of the magnetic tile itself is small, or the image is affected by uneven illumination. In view of these questions, this paper puts forward a new clustering segmentation algorithm based on texture feature. This algorithm uses Gabor function spectra to represent magnetic tile surface texture and then uses a user-defined local product coefficient to modify Gabor energy spectra to get the center number of fuzzy C-means(FCM) clustering. Moreover, the user-defined Gabor energy spectra image is segmented by clustering algorithm. Finally, it extracts the magnetic tile surface defects according to the changes of regional gray characteristics. Experiments show that the algorithm effectively overcomes the noise interference and makes a good performance on accuracy and robustness, which can effectively detect crack,damage, pit and other defects on the magnetic tile surface.

Local pixel patterns

In this paper, a new class of image texture operators is proposed. We firstly determine that the number of gray levels in each B × B subblock is a fundamental property of the local image texture. Thus, an occurrence histogram for each B × B sub-block can be utilized to describe the texture of the image. Moreover, using a new multi-bit plane strategy, i.e., representing the image texture with the occurrence histogram of the first one or more significant bit-planes of the input image, more powerful operators for describing the image texture can be obtained. The proposed approach is invariant to gray scale variations since the operators are, by definition,invariant under any monotonic transformation of the gray scale, and robust to rotation. They can also be used as supplementary operators to local binary patterns(LBP) to improve their capability to resist illuminance variation, surface transformations, etc.