Smooth Color Research Articles

GAN‐Based Multi‐Decomposition Photo Cartoonization

AbstractBackgroundCartoon images play a vital role in film production, scientific and educational animation, video games, and other fields, and are one of the key visual expressions of artistic creation. However, since hand‐crafted cartoon images often require a great deal of time and effort on the part of professional artists, it is necessary to be able to automatically transform real‐world images into different styles of cartoon images. Although cartoon images vary from artist to artist, cartoon images generally have the unique characteristics of being highly simplified and abstract, with clear edges, smooth color shading, and relatively simple textures. However, existing image cartoonization methods tend to create a number of problems when performing style transfer, which mainly include: (1) the resulting generated images do not have obvious cartoon‐style textures; and (2) the generated images are prone to structural confusion, color artifacts, and loss of the original image content. Therefore, it is also a great challenge in the field of image cartoonization to be able to make a good balance between style transfer and content keeping.MethodsIn this paper, we propose a GAN‐based multi‐attention mechanism for image cartoonization to address the above issues. The method combines the residual block used to extract deep network features in the generator with the attention mechanism, and further strengthens the perceptual ability of the generative model to cartoon images through the adaptive feature correction of the attention module to improve the cartoon features of the generated images. At the same time, we also introduce the attention mechanism in the convolution block of the discriminator, which is used to further reduce the image visual quality problem caused by the style transfer process. By introducing the attention mechanism into the generator and discriminator models of the generative adversarial network, our method enables the generated images to have obvious cartoon‐style features while effectively improving the image's visual quality.ResultsA large number of quantitative, qualitative, and ablation experiments are conducted to demonstrate the advantages of our method in the field of image cartoonization and the role of each module in the method.

The Evolution of the Phase Space Structure Along Pitchfork and Period-Doubling Bifurcations in a 3D-Galactic Bar Potential

We investigate how the phase space structure of a Three-Dimensional (3D) autonomous Hamiltonian system evolves across a series of successive Two-Dimensional (2D) and 3D pitchfork and period-doubling bifurcations, as the transition of the parent families of Periodic Orbits (POs) from stability to simple instability leads to the creation of new stable POs. Our research illustrates the consecutive alterations in the phase space structure near POs as the stability of the main family of POs changes. This process gives rise to new families of POs within the system, either maintaining the same or exhibiting higher multiplicity compared to their parent families. Tracking such a phase space transformation is challenging in a 3D system. By utilizing the color and rotation technique to visualize the Four-Dimensional (4D) Poincaré surfaces of section of the system, i.e. projecting them onto a 3D subspace and employing color to represent the fourth dimension, we can identify distinct structural patterns. Perturbations of parent and bifurcating stable POs result in the creation of tori characterized by a smooth color variation on their surface. Furthermore, perturbations of simple unstable parent POs beyond the bifurcation point, which lead to the birth of new stable families of POs, result in the formation of figure-8 structures of smooth color variations. These figure-8 formations surround well-shaped tori around the bifurcated stable POs, losing their well-defined forms for energies further away from the bifurcation point. We also observe that even slight perturbations of highly unstable POs create a cloud of mixed color points, which rapidly move away from the location of the PO. Our study introduces, for the first time, a systematic visualization of 4D surfaces of section within the vicinity of higher multiplicity POs. It elucidates how, in these cases, the coexistence of regular and chaotic orbits contributes to shaping the phase space landscape.

AN EFFICIENT IMAGE PROCESSING BASED IMAGE TO CARTOON GENERATION BASED ON DEEP LEARNING

This paper proposes an approach to convert real life images into cartoon images using image processing. The cartoon images have sharp edges, reduced colour quantity compared to the original image, and smooth colour regions. With the rapid advancement in artificial intelligence, recently deep learning methods have been developed for image to cartoon generation. Most of these methods perform extremely huge computations and require large datasets and are time consuming, unlike traditional image processing which involves direct manipulation on the input images. In this paper, we have developed an image processing based method for image to cartoon generation. Here, we perform parallel operations of enhancing the edges and quantizing the colour. The edges are extracted and dilated to highlight them in the output colour image. For colour quantization, the colours are assigned based on proposed formulation on separate colour channels. Later, these images are combined and the highlighted edges are added to generate the cartoon image. The generated images are compared with existing image processing approaches and deep learning based methods. From the experimental results, it is evident that the proposed approach generates high quality cartoon images which are visually appealing, have superior contrast and are able to preserve the contextual information at lower computational cost.

Facile Synthesis of Multicolored Stacked Quantum Dot Films for Efficient White Light Emission

Quantum dot (QD)-based white light-emitting diodes (LEDs) or white QD-LEDs were successfully fabricated by stacking QD films of primary colors (i.e., red, green, and blue). An ultrathin ZnO film was deposited between each QD layer to facilitate the formation of a tricolor-stacked QD structure. Such stacked QD films effectively suppress the Förster resonance energy transfer between QDs and enable efficient blue light emission, unlike randomly mixed QD films of different colors. The photoluminescence (PL) spectra of various QD films were obtained to study the change in the corresponding color gamut with applied voltage. In addition, QD-LEDs were fabricated based on the PL behavior and electronic band diagrams of QDs of different colors. Maximum luminance and peak EQE of white QD-LED shows 5700 cd/m2 and 1.1% compared to 2200 cd/m2 and 0.3% of QD-LED with mixed QD layer. Finally, a smooth color transition and white light emission were achieved using a blue/green/red stacking sequence for the QDs, which successfully suppressed the energy transfer effect. The overall performance and brightness of the white QD-LEDs synthesized in this study can be further enhanced by developing high-performance blue QDs.

Deriving Coastal Shallow Bathymetry from Sentinel 2-, Aircraft- and UAV-Derived Orthophotos: A Case Study in Ligurian Marinas

Bathymetric surveys of shallow waters are increasingly necessary for navigational safety and environmental studies. In situ surveys with floating acoustic sensors allow the collection of high-accuracy bathymetric data. However, such surveys are often unfeasible in very shallow waters in addition to being expensive and requiring specific sectorial skills for the acquisition and processing of raw data. The increasing availability of optical images from Uncrewed Aerial Vehicles, aircrafts and satellites allows for bathymetric reconstruction from images thanks to the application of state-of-the-art algorithms. In this paper, we illustrate a bathymetric reconstruction procedure involving the classification of the seabed, the calibration of the algorithm for each class and the subsequent validation. We applied this procedure to high-resolution, UAV-derived orthophotos, aircraft orthophotos and Sentinel-2 Level-2A images of two marinas along the western Ligurian coastline in the Mediterranean Sea and validated the results with bathymetric data derived from echo-sounder surveys. Our findings showed that the aircraft-derived bathymetry is generally more accurate than the UAV-derived and Sentinel-2 bathymetry in all analyzed scenarios due to the smooth color of the aircraft orthophotos and their ability to reproduce the seafloor with a considerable level of detail.

Graph Jigsaw Learning for Cartoon Face Recognition.

Cartoon face recognition is challenging as they typically have smooth color regions and emphasized edges, the key to recognizing cartoon faces is to precisely perceive their sparse and critical shape patterns. However, it is quite difficult to learn a shape-oriented representation for cartoon face recognition with convolutional neural networks (CNNs). To mitigate this issue, we propose the GraphJigsaw that constructs jigsaw puzzles at various stages in the classification network and solves the puzzles with the graph convolutional network (GCN) in a progressive manner. Solving the puzzles requires the model to spot the shape patterns of the cartoon faces as the texture information is quite limited. The key idea of GraphJigsaw is constructing a jigsaw puzzle by randomly shuffling the intermediate convolutional feature maps in the spatial dimension and exploiting the GCN to reason and recover the correct layout of the jigsaw fragments in a self-supervised manner. The proposed GraphJigsaw avoids training the classification model with the deconstructed images that would introduce noisy patterns and are harmful for the final classification. Specially, GraphJigsaw can be incorporated at various stages in a top-down manner within the classification model, which facilitates propagating the learned shape patterns gradually. GraphJigsaw does not rely on any extra manual annotation during the training process and incorporates no extra computation burden at inference time. Both quantitative and qualitative experimental results have verified the feasibility of our proposed GraphJigsaw, which consistently outperforms other face recognition or jigsaw-based methods on two popular cartoon face datasets with considerable improvements.

BONE FLOUR FROM SUCKERMOUTH FISH (Pterygoplichthys pardalis) AND TILAPIA FISH (Oreochromis mossambicus)

Fish is often used as a protein source in food. Fish has good nutritional content for the body such as protein, vitamin, mineral, and unsaturated fatty acid. Pterygoplichthys pardalis and Oreochromis mossambicus are some of the local fishes that are frequently found in a river in Indonesia, also Asia. People use their meat as food. Unfortunately, people do not use fishbones. In this research, we processed the fishbone into flour which could be used as food or supplement. Fishes were collected from the breeder in January to May 2019. Bone processing methods carried out by separation of fish meat and bone, continued with bone flour processing using oven and grinder. According to the proximate analysis revealed that P. pardalis bone flour contained 25.047% protein, 10.478% fat, 0.656% water, 59.463% ash, and 4.353% carbohydrate. O. mossambicus also contained 36.929% protein, 11.942% fat, 2.575% water, 45.721% ash, and 2.833% carbohydrate. From these results, protein in P. pardalis gave a higher value than O. mossambicus. Bone flour from both fishes showed a smooth texture and whitish color. Bone flour from fish has good prospects to be developed to get complete analysis in food technology. Bone flour from suckermouth fish played important role in aquaculture and supported the river biodiversity.

Candida Berkh. (1923) Species and Their Important Secreted Aspartyl Proteinases (SAP) Genes Isolated from Diabetic Patients

Background: Candida Berkh. (1923) occurs naturally in the body. But it becomes opportunistic fungi, meaning that it infects humans when there is any weakening of the immune system, such as exposure to chemotherapy, diabetes, or organ transplantation. Most species of Candida grow at a temperature between 20-40 °C and have a pH of 3-8. Human pathogens of Candida species include C. albicans, C. glabrata, C. lusitaniae, C. parapsilosis, C. tropicalis and C. utili. C. albicans has many virulence factors that facilitate injury process. Virulence factors are considered as a measure of pathogenicity, and it is in the form of fungal toxins, enzymes, or cell structures that facilitate infection, as well as pathogen resistance in different conditions. This study aimed to investigate the frequency of some secreted aspartyl proteinases (SAP) genes from some Candida species isolated from diabetic patientsMethods: Candida spp. were identified on CHROMagar medium by color of each species after incubation at 37 °C for 48 hours such as: C. krusei, C. albicans, C. glabrata, and C. tropicalis. Germ tube formation test was used to distinguish between germ tube-forming species, such as C. albicans and C. dubliniensis , from those that do not produce germ tube. A portion of the isolation was taken and placed in a test tube containing 0.5 ml of serum, and then incubated at 37 °C for 2-4 hours. A drop of serum was taken out and examined under a microscope for the presence of the germ tube. Growth at 45 °C, has the advantage of distinguishing between C. albicans and C. dubliniensis by culturing Candida spp. on SDA medium and, incubation for 48-72 hours at 45 °C.Results: The results of isolation and diagnosis showed that Candida species grew at 37 °C for 48 hours on SDA medium, the shape of the colonies was round or oval-convex, and creamy white, shiny and smooth color. The results of the microscopic examination of the cells were spherical or oval, C. albicans was distinguished by its ability to grow at 45 °C and its ability to form the germ tube. The surface growth test showed the ability of C. tropicalis to grow surface on SDB medium. The medium of CHROMagar showed that C. albicans were light green in color. C. glabrata showed a pale pink color, while C. tropecalis showed a blue color and C. dublineiensis was dark green. DNA extracted samples, including 20 isolates, were used for four species of Candida, 1-9 C. albicans, 10-16 C. glabrata, 17-18 C. dubliniensis and 19-20 C. tropicalis. Parts of the body (mouth, vagina, Urine) detect SAP1 and SAP7 genes by PCR, and after electrophoresis of the PCR product, the results were positive for all Candida species studied as all isolates that contained SAP1 (578bp) and SAP7 (466bp).Conclusion: The SAP genes are among the main virulence factors for the occurrence of candidiasis. SAP1 and SAP7 genes are responsible for digesting and breaking down protein to penetrate the host's tissues.

Start-up of an aerobic granular sludge system from stored granules: Evaluating the impact of storage period on biomass activity and stability and the effect of temperature on nitrification and phosphorus removal rates

Aerobic granular sludge (AGS) has been considered a breakthrough within the wastewater treatment sector. However, the long reactor start-up for the formation of granules is challenging and may hinder the spread of this technology. To circumvent this obstacle, inoculation of the reactors with pre-formed granules from existing plants is an interesting approach. In this context, issues related to biomass storage becomes very relevant. In this study, reactivation of aerobic granular biomass after storage was evaluated in a sequencing batch reactor (SBR) designed for achieving simultaneous organic matter, nitrogen and phosphorus removal. Two different scenarios, short (40 days) and long (180 days) storage periods, were assessed, and their influence on the granules physical properties and bioactivity was addressed. The results revealed that the granules stored for a shorter period showed higher resistance to breakage and underwent smooth color changes. On the other hand, the biomass stored for a longer period acquired a dark color and was more susceptible to disruption during reactivation. The granules stored for 6 months become swollen and exhibited an irregular morphology and fluffy structure within the first days of reactivation. Consequently, their settling properties were adversely affected, and some parameters such as the food-to-microorganism ratio had to be adjusted to prevent granules disintegration. Regarding the bioactivity of important microbial functional groups, COD removal was rapidly restored within a few days of SBR operation with the biomass stored for a shorter period. However, it took longer for the biomass stored for 180 days to reach the same performance observed for the granules stored for 40 days. A similar trend is valid for nitrification. In the experiments with sludge stored for a longer time, it took almost twice as long to reach effluent ammonium concentrations lower than 1 mg NH4+-N L−1 compared to the test using biomass stored for 40 days. Phosphate removal was strongly affected by biomass storage, especially after 180 days of inactivity, a condition found to be detrimental for polyphosphate-accumulating organisms. Finally, cycle tests were also conducted to assess substrate conversion rates for comparison between different trials and evaluate the influence of temperature (10–35 °C) on nitrification and phosphate removal rates.

<italic>L</italic><sub>0</sub> Optimization Using Laplacian Operator for Image Smoothing

<p indent=0mm>Image smoothing often leads to the loss of image details and distortion because of over smoothing. An image smoothing method is presented which combines<inline-formula id=inline3><mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML display=inline><mml:mrow><mml:msub><mml:mi>L</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>optimization and the second-order Laplacian operator. Laplacian operator is used to constrain the color change of the image, and <inline-formula id=inline4><mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML display=inline><mml:mrow><mml:msub><mml:mi>L</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>optimization is used to minimize the change of the color gradient, so as to achieve the purpose of smooth color transition of the image. In order to keep the edge features of the image better in the process of smoothing, Sobel operator is introduced as the regular term of energy function, and the alternating solution strategy is adopted to solve the energy function. In the experiment, using the classical image in the field of image smoothing and the image obtained through network engine, the proposed method is compared qualitatively and quantitatively with 6 smoothing methods and 7 denoising methods. The experimental results show that the proposed method can reduce the loss of image details while smoothing the image, effectively deal with the phenomenon of stepped edges and color block distribution in the image smoothing, and effectively remove various noises in the image. And the peak signal-to-noise ratio and running time of the proposed method are improved compared with other methods.

Технология приготовления функционального продукта из конины в соусе

Introduction. The priority task of the food industry is to provide population with functional products since the health of nation and its people largely depends on the diet. New formulations and technologies for meat products broaden the range of functional foods. Flaxseed oil is an excellent source of functional ingredients as it is rich in polyunsaturated fatty acids and tocopherols. The present research featured horsemeat as a promising raw material of high nutritional and biological value. Horsemeat is a traditional food source for many nations. The research objective was to develop a new technology for horsemeat in sauce and to select the optimal thermal processing method.&#x0D; Study objects and methods. The authors tested several methods of heat treatment and used a standard nine-point scale to assess the sensory properties of the finished product. The experiment involved standard physicochemical and organoleptic research methods. The color characteristics were described using digital image processing.&#x0D; Results and discussion. The study delivered a new formulation of sauce with flaxseed oil, which improved the quality of the fat component of the finished product. The new sauce proved to be rich in polyunsaturated fatty acids and possessed high sensory and technological properties. A comparative analysis of the heat treatment methods included traditional frying and stewing, cooking in a steam convection oven, and a sous-vide technology. The sous vide technology appeared to have the best structural-mechanical, physicochemical, and sensory properties. Software processing of digital images made it possible to compare the color of raw, semifinished, and cooked meat samples. The traditional cooking methods of frying and stewing showed the most pronounced changes in the color, while the sous-vide technology demonstrated a smooth color change. As for the quality of the finished product, it proved to satisfy 40% of daily intake for polyunsaturated fatty acids and 20% for tocopherol, which makes the product functional.&#x0D; Conclusion. The new technology made it possible to expand the range of functional meat products. The new digital image processing program helped to register changes in shape and color of meat samples after various heat treatment methods.

Video Vectorization via Bipartite Diffusion Curves Propagation and Optimization.

We propose a new video vectorization approach for converting videos in the raster format to vector representation with the benefits of resolution independence and compact storage. Through classifying extracted curves in each video frame into salient ones and non-salient ones, we introduce a novel bipartite diffusion curves (BDCs) representation in order to preserve both important image features such as sharp boundaries and regions with smooth color variation. This bipartite representation allows us to propagate non-salient curves across frames such that the propagation, in conjunction with geometry optimization and color optimization of salient curves, ensures the preservation of fine details within each frame and across different frames, and meanwhile, achieves good spatial-temporal coherence. Thorough experiments on a variety of videos show that our method is capable of converting videos to the vector representation with low reconstruction errors, low computational cost, and fine details, demonstrating our superior performance over the state of the art. We also show that, when used for video upsampling, our method produces results comparable to video super-resolution.

Automatic portrait image pixelization

Pixelization is one of the most distinctive image stylization methods, and it is often used in game production, icon design, and advertising printing. One of the most popular examples is portrait pixel art, which retains both the features and imagination of a character. However, the difficulty of pixelization in production and time consumption discourages many untrained people from working in pixel art. In this paper, we propose an automatic pixelization algorithm for portrait images based on Simple Linear Iterative Clustering (SLIC) and Fuzzy Iterative Self-Organizing Data Analysis (FISODATA) algorithms. Several improvements have been made for portrait images using superpixels reordering, cascade object detection, gaussian bilateral filtering, and feature edge enhancement. Our algorithm is particularly well suited for pixelating natural portrait images which have smooth color transition. The proposed algorithm not only satisfies the requirements of clear edges and limited colors of pixel images, but also automatically determines the width and height of the output image and the size of the palette through the image, avoiding intensive human involvement on the resulting image. We compared the results obtained by our proposed algorithm with those of manual pixel art and existing methods. Experimental results show that our algorithm can produce a unique style between realism and abstraction.

A delay in sampling information from temporally autocorrelated visual stimuli

Much of our world changes smoothly in time, yet the allocation of attention is typically studied with sudden changes – transients. A sizeable lag in selecting feature information is seen when stimuli change smoothly. Yet this lag is not seen with temporally uncorrelated rapid serial visual presentation (RSVP) stimuli. This suggests that temporal autocorrelation of a feature paradoxically increases the latency at which information is sampled. To test this, participants are asked to report the color of a disk when a cue was presented. There is an increase in selection latency when the disk’s color changed smoothly compared to randomly. This increase is due to the smooth color change presented after the cue rather than extrapolated predictions based on the color changes presented before. These results support an attentional drag theory, whereby attentional engagement is prolonged when features change smoothly. A computational model provides insights into the potential underlying neural mechanisms.

Light intensity design as a fishing tool on liftnet, with pulse width modulation system based on microcontroller

Fishing can be done in various ways, including by utilizing lights as fishing tools. The lights used for fishing tools are varied, ranging from torch lights, pressure paraffin lamp, fluorescent lamps (TL, PL, SL, CFL), mercury, and various types of led. However, light transition between one colors to another often scares the fish, driving them out of catchable area shocked by the color change. One solution to address this problem is by smoothly switching the color of the lamp using Pulse Width Modulation (PWM) system on the microcontroller. The color used are the lamp with basic colors of red, green and blue. With power capacity of 50Watt/12Volt, this lamp is classified as High Power Led (HPL) lamp. The light can be free- adjusted, where each lamp can be turned on by its own light or can also be turned on in combination. It can slowly be switch on from an off position to maximum and also can be dimmed from maximum to off. Thus the intensity of the light can be controlled. The HPL and control sections were created separately. Tools and materials used are consist of push-button, microcontroller, optocoupler, mosfet and Red, Green and Blue HPL, Radio-meter (ILT5000 Research Radiometer), Voltmeter, and Amperemeter. The method used was experimental in both laboratory and field. The result of research is in the form of RGB HPL lamp which can be adjusted through control system, such as adjusment for each lamp, or light combination with smooth color transition. Thus, when this technology is applied as fishing tool in liftnet fishing, the targeted fish would still remain on catchable area.

A Plasmonic Painter's Method of Color Mixing for a Continuous Red-Green-Blue Palette.

The ability of mixing colors with remarkable results had long been exclusive to the talents of master painters. By finely combining colors in different amounts on the palette, intuitively, they obtain smooth gradients with any given color. Creating such smooth color variations through scattering by the structural patterning of a surface, as opposed to color pigments, has long remained a challenge. Here, we borrow from the painter's approach and demonstrate color mixing generated by an optical metasurface. We propose a single-layer plasmonic color pixel and a method for nanophotonic structural color mixing based on the additive red-green-blue (RGB) color model. The color pixels consist of plasmonic nanorod arrays that generate vivid primary colors and enable independent control of color brightness without affecting chromaticity by simply varying geometric in-plane parameters. By interleaving different nanorod arrays, we combine up to three primary colors on a single pixel. Based on this, two- and three-color mixing is demonstrated, enabling the continuous coverage of a plasmonic RGB color gamut and yielding a palette with a virtually unlimited number of colors. With this multiresonant color pixel, we show the photorealistic printing of color and monochrome images at the nanoscale, with ultrasmooth transitions in color and brightness. Our color-mixing approach can be applied to a broad range of scatterer designs and materials and has the potential to be used for multiwavelength color filters and dynamic photorealistic displays.

Region of interest extraction for image quality assessment

Print quality (PQ) is most important in the printing industry. To detect and analyze print defects is an effective solution to improve print quality. As the different types of print defects appear in different regions of interest (ROI) in the digital image of a scanned page, extracting the different ROIs helps to detect and analyze the printer defect. This paper proposes a method to extract different ROIs based on the digital image object map [1], which includes three different labels: raster (images or pictures), vector (background and smooth gradient color areas), and symbol (symbols and texts). Our ROI extraction method will extract four kinds of ROIs based on these three labeled objects. So we need to distinguish the background area and smooth gradient color area (color vector) from other vector objects. The process of the ROI extraction method includes four parts; and each part will extract one kind of ROI. For the color vector and background ROI extraction part, we develop two approaches: one is to obtain the maximum area rectangular ROI; and the other approach is to extract the deepest rectangular ROI. With both of these two methods, we use a greedy algorithm to gather additional useful ROIs. In the final result of the ROI extraction process, we only save the left top and right bottom positions for each ROI. In the end, we design a Matlab GUI Tool and label the ROI ground truth manually. We calculate the intersection over union (IoU)) between the ROI extraction result and the ROI manually labeled ground truth to evaluate our ROI extraction algorithm, and check whether it is good enough to crop different ROIs from the image of the scanned page to detect and analyze print defects.

Improved skin lesions detection using color space and artificial intelligence techniques

Background: Automatic skin lesion image identification is of utmost importance to develop a fully automatized computer-aided skin analysis system. This will be helping the medical practitioners to provide skin lesions disease treatment more efficiently and effectively.Material and method: In this article, two image processing techniques for accurate detection of skin lesions have been proposed. In first technique, the optimization of edge detection has been carried out by using a branch of artificial intelligence called nature inspired algorithm. Ant colony optimization (ACO) is used to increase effectiveness of edge detection in skin lesion. The second technique deals with the color space-based split-and-merge process in combination with global thresholding segmentation and edge smoothing operations.Result: The performance of both techniques has been measured by entropy performance evaluation parameter. The results show remarkable improvement in output images obtained by Canny edge detection technique optimized by ACO in comparison with ACO-Sobel, ACO-Prewitt and Edge Smoothing-Color Space techniques.Conclusion: ACO-Canny Edge detection technique shows far better effieciency for skin lesion detection as compared to ACO-Sobel, ACO-Prewitt and Edge Smoothing Color Space technique.

A Review on Dyerophytum indicum Kuntze

Dyerophytum indicum Kuntze. Belongs to family Plumbaginaceae 27 genera with 650 species and locally is called as Lal-chitrak found Plant was first reported in Oman and they listed Dyerophytum indicum as endangered species. Flowers are red in color, bloom all the year. Individual flower is up to 1/2; inches It is an under-shrub with perfoliate, very thick and coriaceous leaves. The leaves are covered with scurfy scales, flowers are reddish and dense, paniculate spikes and flowers in the month of October-February. Capsules are circumcises at the base and splitting into five valves. Seeds are pyriform with smooth texture and dark brown color. 5 lobed stamens free ovary is present with more or less 5 gonous. The plant is being used in snake bite, anti-allergic and tribal people used it as abortificient. The ancient literature reveals that it contains different phyoconstituent like alkaloids, glycosoids, flavonoids, tannins, terpenoids and other primary metabolites. These is an rare plant so not many literature is reported.

A delay in sampling information from temporally autocorrelated visual stimuli

Much of our world changes smoothly in time, yet the allocation of attention is typically studied with sudden changes - transients. A sizeable lag in selecting feature information is seen when stimuli change smoothly. Yet this lag is not seen with temporally uncorrelated rapid serial visual presentation (RSVP) stimuli. This suggests that temporal autocorrelation of a feature paradoxically increases the latency at which information is sampled. To test this, participants are asked to report the color of a disk when a cue was presented. There is an increase in selection latency when the disk's color changed smoothly compared to randomly. This increase is due to the smooth color change presented after the cue rather than extrapolated predictions based on the color changes presented before. These results support an attentional drag theory, whereby attentional engagement is prolonged when features change smoothly. A computational model provides insights into the potential underlying neural mechanisms.