Abstract: Harbor water area extraction is a key step in nearshore environment pollution surveillance using remote sensing image processing techniques. This letter proposes the definition circle (DC) model of color gradient to describe color fluctuations in harbor water surface areas based on pan-sharpened remote sensing images. The DC model includes two steps: center setting and radius tuning. In the center setting process, labeled training set pixels are selected in the red, green, and blue color space. Then, center setting is completed in the hue, saturation, and intensity color space using the perceptron model. In the radius tuning process, positive and negative sample pixels are used to tune the radius value. After these two steps, the DC model can describe the color gradient of a water surface area and provide accurate harbor water area extraction. A series of experiments shows that the proposed DC model is robust and performs better than other extraction methods based on pan-sharpened remote sensing images.

Abstract: We exploit human color metamers to send light-modulated messages decipherable by cameras, but camouflaged to human vision. These time-varying messages are concealed in ordinary images and videos. Unlike previous methods which rely on visually obtrusive intensity modulation, embedding with color reduces visible artifacts. The mismatch in human and camera spectral sensitivity creates a unique opportunity for hidden messaging. Each color pixel in an electronic display image is modified by shifting the base color along a particular color gradient. The challenge is to find the set of color gradients that maximizes camera response and minimizes human response. Our approach does not require a priori measurement of these sensitivity curves. We learn an ellipsoidal partitioning of the 6-dimensional space of base colors and color gradients. This partitioning creates metamer sets defined by the base color of each display pixel and the corresponding color gradient for message encoding. We sample from the learned metamer sets to find optimal color steps for arbitrary base colors. Ordinary displays and cameras are used, so there is no need for high speed cameras or displays. Our primary contribution is a method to map pixels in an arbitrary image to metamer pairs for steganographic camera-display messaging.

Abstract: The invention relates to a design method of a music color lamp controller based on rhythm following. A music rhythm extraction algorithm based on waveform energy variation characteristic detection is employed and an acoustic characteristic and color lamp space mapping relation model is employed to process the audio signal, a music rhythm detection effect is achieved through a short-time energy extreme value judgment, and the time point information of a music rhythm is achieved. At the time point of music rhythm appearance, the short-time signal of the time point is subjected to spectrum analysis and processing, real-time acoustic energy and frequency domain characteristic parameters are obtained in real time, the mapping relation models of pitch and color domain, timbre and saturation, and sound intensity and brightness are established, a color lamp color is changed as a color obtained by the frequency domain information conversion of an audio waveform at the point, and the color lamp color change and music rhythm change synchronization is realized. According to the method, a color gradient mechanism is adopted in color lamp driving, and the soft change of a light effect is realized.

Abstract: Face liveness detection is widely used to detect face spoofing attacks. Most existing face liveness detection methods are mainly based on texture information of face images in the gray-scale space which ignored the chrominance information and other feature differences. In this paper, we introduced a novel modified color gradient feature into face liveness detection which used variant color roberts cross operator. This method can extract the color gradient information from the live faces or fake faces so that the proposed method has potential to achieve a better performance. Extensive experimental results on benchmark databases showed that the proposed variant color-gradient feature was very effective for face liveness detection.

Abstract: Color is an effective communication media in the objects of Art and historical (A&H) significance. However, as age increases, the objects become prone to color change through weather conditions, handling, display or preservation tasks. Therefore, to monitor the overall color change or to detect discolored area, it is important to precisely visualize the colored surface. This paper shows that RGB values computed using surface reflectance in (400–1000) nm wavelength range are capable to automatcially highlight any subtle color defect. Classical carpets are chosen to exemplify the outputs in this study. The extended CIE color matching functions based visualization method is most effective to render each multivariate data point by a single color. The defective areas of the surface in the resulting images appear strong to be detected readily. However, the conventional RGB colors fail mostly to reveal these color defects. Since spectral imaging is non-destructive and wide-area resolved, presented technique offers a comprehensive understanding of the color conditions of the A&H objects. So the visualization method should help the conservators to make informative decisions about different conservation and restoration strategies.

Abstract: The invention provides an image fusion method, a device and a system. The method comprises the steps that an object mask in a source image is reduced and expanded to acquire a fusion region with an outer boundary and an inner boundary; a model which comprises a composite coefficient and is based on the weighting function of the object gradient is defined in the fusion region, wherein the model comprises a smoothing term, and the weight of the smoothing term is smaller when the color gradient of the source image is larger, and the weight of the smoothing term is larger when the color gradient of the source image is smaller; the model is calculated to acquire the composite coefficient which minimizes the value of the model; and an object and a target image in the object mask are synthesized according to the composite coefficient to generate a composite result image.

Abstract: Colors are displayed in different ways on various devices, such as cameras, screens and printers. In order to achieve consistent appearance on these devices, color management is usually used, where the core part is Gamut Mapping Algorithm (GMA). However, the widely adopted Point-wise Gamut Mapping Algorithms (PGMAs) have been restricted to compromise between color accuracy and details. In this work, we firstly split color space into small cubes through sampling colors from it. Then, we built a 26-neighbored graph with the sample colors as vertexes and perceptual color differences between adjacent vertexes as weights. Based on the above graph, a new Multi-source Shortest Paths Algorithm (MSS-PA) is proposed to establish color mapping relationships between out-of-gamut colors and colors in gamut boundary. In the MSSPA, distance of shortest path between nonadjacent vertexes are used to replace those calculated directly using CIEDE2000, which is useful to measure large color difference. Experimental results show that our method achieves superior performance on the aspect of keeping accuracy and preserving details compared with HPMinDE and SGCK.

Abstract: The Fast Development of the image capturing in digital form leads to the availability of large databases of images. The manipulation and management of images within these databases depend mainly on the user interface and the search algorithm used to search these huge databases for images, there are two search methods for searching within image databases: Text-Based and Content-Based. In this paper, we present a method for content-based image retrieval based on most used colors to extract image features. A preprocessing is applied to enhance the extracted features, which are smoothing, quantization and edge detection. Color quantization is applied using RGB (Red, Green, and Blue) Color Space to reduce the range of colors in the image and then extract the most used color from the image. In this approach, Color distance is applied using HSV (Hue, Saturation, Value) color space for comparing a query image with database images because it is the closest color space to the human perspective of colors. This approach provides accurate, efficient, less complex retrieval system.

Abstract: The invention discloses a color gradient graphic display method and device, relates to the technical field of information, and aims to realize color gradient display for a graph along a radian direction and improve the color gradient display effect of the graph. The method comprises the following steps: firstly, acquiring a graph needing color gradient display; secondly, partitioning the graph into a plurality of areas, wherein extension lines of dividing lines corresponding to the plurality of areas intersect at a preset point; thirdly, configuring different colors for the areas according to a preset color gradient rule; and lastly, performing color gradient display on the graph. The color gradient graphic display method and device are suitable for color gradient display of the graph.

Abstract: We present a method to create vector cliparts from photographs. Our approach aims at reproducing two key properties of cliparts: they should be easily editable, and they should represent image content in a clean, simplified way. We observe that vector artists satisfy both of these properties by modeling cliparts with linear color gradients, which have a small number of parameters and approximate well smooth color variations. In addition, skilled artists produce intricate yet editable artworks by stacking multiple gradients using opaque and semi-transparent layers. Motivated by these observations, our goal is to decompose a bitmap photograph into a stack of layers, each layer containing a vector path filled with a linear color gradient. We cast this problem as an optimization that jointly assigns each pixel to one or more layer and finds the gradient parameters of each layer that best reproduce the input. Since a trivial solution would consist in assigning each pixel to a different, opaque layer, we complement our objective with a simplicity term that favors decompositions made of few, semi-transparent layers. However, this formulation results in a complex combinatorial problem combining discrete unknowns (the pixel assignments) and continuous unknowns (the layer parameters). We propose a Monte Carlo Tree Search algorithm that efficiently explores this solution space by leveraging layering cues at image junctions. We demonstrate the effectiveness of our method by reverse-engineering existing cliparts and by creating original cliparts from studio photographs.