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.

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.

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.

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.

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.