Abstract: According to an aspect of the present invention, the first filters, which correspond to the two or more first colors that contribute to obtaining a brightness signal more than the second colors, are disposed within each pixel line in first direction to the fourth direction of the color filter arrangement, and it is configured so that the ratio of the number of pixels of the first colors corresponding to the first filters is larger than the ratio of the number of pixels of each color of the second colors corresponding to the second filters of two or more colors other than the first colors. Accordingly, the degree of reproducibility of the synchronization processing in a high-frequency wave area can be increased and the aliasing can be suppressed.

Abstract: A method for processing an image is disclosed. The method comprises: • - identifying a group of keypoints in the image; • - for each keypoint of the group; • • a) calculating a corresponding descriptor array including a plurality of array elements, each array element storing values taken by a corresponding color gradient histogram of a respective sub-region of the image in the neighborhood of the keypoint; • b) generating at least one compressed descriptor array by compressing at least one portion of the descriptor array by means of vector quantization using a codebook (CBK) comprising a plurality of codewords (CW).

Abstract: An image processing apparatus comprises: a unit configured to generate a gradation cluster by determining color regions belonging to the same gradation among a plurality of color regions using gradation attribute of boundary, and to generate gradation cluster information including information about a color region belonging to the generated gradation cluster and a gradation type of the gradation cluster; a unit configured to generate a gradation parameter for each gradation region using the color region, the color gradient information, and the gradation cluster information; a unit configured to integrate color regions belonging to the same gradation using the gradation cluster information; and a unit configured to generate a contour vector description based on a color region after integration, and to generate vector data of the gradation region based on the contour vector description and the gradation parameter.

Abstract: A control device mounted in an image forming apparatus includes a region searching for unit searching for a region adapted to measure colors in an image; a color measurement unit configured to measure colors of the superimposed color toner image in the region; a storage unit storing measured colors and densities proportional to area ratios of primary color toner images in the superimposed color toner image in the region; and a correction amount determination unit determine correction amounts corresponding to the setting values expressing the tone reproduction curves to minimize the difference between the measured colors and the reference colors.

Abstract: In this paper, we propose a novel segmentation algorithm for color images. This method is a combination of edge information with region information and a geometric active contour without re-initialization, called distance regularized level set evolution. The information given by a new edge detector using morphological gradient is more accurate than normal gradient computing methods for color images. And the information of the region containing objects is relied on Chan-Vese minimal variance criterion. With both of these information, the model can have its initial contour that is more flexible to construct anywhere, fast to evolve and quite exact to stop at the boundary of objects. The suggested algorithm has been applied on natural color images with good performance. Some experimental results have shown to compare our model with others with respect to accuracy and computational efficiency.

Abstract: Automatic global color transfer is a challenging problem in image editing. In this paper, we propose a novel color transfer method, which is based on the gradient-aware decomposition and the color distribution mapping. Firstly, a gradient-aware decomposition model is established to separate the target image into the base and detail layers. Then, the colors of each separated base layer are enforced to match those of a given reference image by Pitie's multi-dimensional probability density function transfer method. After that, all mapped base layers are combined with corresponding boosted detail layers to produce the final output. The experiments demonstrate that our method can achieve a visual satisfied result without post-processing gradient correction.

Abstract: Visual inspection of alpha channel values is aided by displaying a partially transparent image rendered over an animated background pattern. The background pattern is user-specified or chosen automatically. The background pattern has colors, shapes, position, orientation, magnification, and distortion. The visual appearance of the background pattern is automatically altered, and the partially transparent image is redisplayed, this time rendered over the altered background pattern. The background pattern may scroll, rotate, change shape, pulse, morph shape, and/or change colors during animation. The background includes a checkerboard or another tessellation, a color gradient, a transparency heat map, a procedurally generated texture, and/or other patterns. A color identified in the partially transparent image may provoke use of a complementary color in the background. The image whose transparency is being visually inspected zooms independently of the background pattern. Animation of the background helps reveal unwanted transparency values, which the user edits as desired.

Abstract: In this paper an algorithm for gradient domain color-to-gray conversion is described. By enhancing the luminance gradient with the chromatic difference in CIELAB space, a gradient field is created to construct the resulting gray-scale image using a Poisson equation solver. In our algorithm, we develop a modulated luminance gradient enhancement to produce artifact-free and salience-preserving grayscale images. A gradient sign control function is defined for isoluminance color images to keep the correct color ordering.

Abstract: Visualization of water depth in geographical maps is limited by contour line density and by human ability to distinguish a subtle difference of the color gradient at a specific map scale. We were interested in whether it is it possible to increase the accuracy of subjective assessment of the bathymetric information coded by color intensity when visual observation would be complemented with haptic feedback presented as a function of the water depth. This paper describes the results of an evaluation of the new interaction technique that has potential to increase the estimation accuracy of color-coded information presented in a two-dimensional space of a topographic map. In particular, it was demonstrated that untrained subjects could accurately navigate between two geographic locations on the map of the lake by providing the necessary depth when values of the color intensity were associated with haptic feedback presented as a function of the lake floor. A comparative evaluation of the accuracy of navigation was carried out visually, using a regular mouse, and instrumentally with the StickGrip haptic device. The accuracy of navigation with the StickGrip haptic device appears to be higher by 14.25% to 23.5% in a range of bathymetric data of 40–140 m. We confirmed that a kinesthetic sense of distance to the surface of interaction (tablet) and self-perception of the finger joint-angle positions enhance the accuracy in distinguishing the color intensity of the digital map. The new mobile technique can be used as an alternative to the earlier non-mobile force-feedback devices for interaction with geospatial data.

Abstract: In this paper, we propose an orthophotoplan segmentation method based on watershed algorithm combined with an efficient region merging strategy for roof detection. The preliminary segmentation is obtained by the watershed algorithm with an optimal couple of colorimetric invariant/color gradient optimized for the application. The use of the appropriate couple of invariant/gradient permits to limit illumination changes (shadows, brightness, etc) affecting the images. Even if the watershed based results are good, the images are over-segmented. That is why, a region merging procedure is proposed. This procedure uses a merging criteria based on 2D modeling of roof ridges and region features adapted to the orthophotoplan particularities. The proposed strategy is evaluated on 100 real roof images with a ground truth image segmentation in order to demonstrate the effectiveness and the reliability of the proposed approach.

Abstract: A system and method for matching spot colors in a PDL document with actual printed output is disclosed. A pre-press workflow application identifies spot colors in a PDL document and creates a table of potential substitute color tiles, each having color characteristics similar to the original spot color. These tiles are then printed in a “swatch page” of numerically assigned colors and reviewed by the user for potential selection over the original spot color values. A substitute color may then be selected from the swatch page and the pre-assigned numerical value for the selected color tile input into the workflow application. The PDL document is then altered to record the color change. The resulting printed document more closely matches the desired spot color and the process can be repeated for any print environment to allow for more consistent printing results and lower print job costs.

Abstract: Color image data is compressed by determining the number of colors within a cell of an input image, each cell comprising an N×M array of pixels; in response to determining that the number of colors is greater than a first predetermined threshold, compress the cell using lossy compression; and in response to determining that the number of colors is less than the first predetermined threshold, reduce the number of colors.

Abstract: This paper proposes a feature extraction approach inspired by the Scale Invariant Feature Transform (SIFT) algorithm. We compute the color gradient based on Principal Component Analysis (PCA). To discover the correct keypoints position, we use the hue information of the image and apply our own color corner detection algorithm, described further in this article. We present our results, both on images of human eye iris affected by melanoma and also on images representing color textures of healthy iris. Then we conclude this paper.

Abstract: A method for processing an image, including: identifying a group of keypoints in the image; for each keypoint, calculating a corresponding descriptor array including plural array elements, each array element storing values taken by a corresponding color gradient histogram of a respective sub-region of the image in the neighborhood of the keypoint; for each keypoint, subdividing the descriptor array in at least two sub-arrays each including a respective number of elements of the descriptor array, and generating a compressed descriptor array including a corresponding compressed sub-array for each of the at least two sub-arrays, each compressed sub-array obtained by compressing the corresponding sub-array by vector quantization using a respective codebook; exploiting the compressed descriptor arrays of the keypoints for image analysis. For each keypoint of the group, the subdividing is based on correlation relationships among color gradient histograms with values stored in the elements of the descriptor array of each keypoint.

Abstract: A method of creating an ensemble of visible color reference patches first adds a set of starting colors to a queue. The process then finds a candidate color within a color selection zone that is furthest away from colors existing in the queue. This candidate color is then selected by placing it in the queue. The steps of finding and selecting are repeated until a target number of selected colors is reached. The process then generates visible color patches of the selected colors for forming the ensemble.

Abstract: In this system we improved the performance of an automatic system for extracting leaf contour. The proposed leaf contour extraction method consists of three major procedures: the detection of four edge points, and contour tracing. Leaf detection includes two stages: feature extraction and matching. For the leaf contour extraction part, we present a new technique for automatically identifying the contour of a leaf in an image. For contour tracing, an Intelligent Scissor (IS) algorithm is applied. The color gradient magnitude and Canny edge detection are analyzed and included as the cost terms of the Intelligent Scissor algorithm. The color gradient magnitude cost term is implemented so that it can act directly on the three components of the color image. For the third procedure, we implement of the performance improvement. The main idea about proposed method is when the program detected the incorrect four edge points, we using the mouse and clicked the right position instead of the incorrect one.

Abstract: A control device mounted in an image forming apparatus includes a region searching for unit searching for a region adapted to measure colors in an image; a color measurement unit configured to measure colors of the superimposed color toner image in the region; a storage unit storing measured colors and densities proportional to area ratios of primary color toner images in the superimposed color toner image in the region; and a correction amount determination unit determine correction amounts corresponding to the setting values expressing the tone reproduction curves to minimize the difference between the measured colors and the reference colors.

Abstract: PROBLEM TO BE SOLVED: To vectorize a gradation portion of an input image at a high speedSOLUTION: An input image is divided into plural color areas on the basis of a color difference to calculate color gradient information at a boundary Then, using the color gradient information, a gradation attribute indicating a characteristic of the color gradient at the boundary is determined The color areas belonging to the same gradation among the plural color areas are determined to create a gradation cluster, and create gradation cluster information including information relating to the color area belonging to the created gradation cluster and a kind of the gradation of the gradation cluster Using the color area, the color gradient information and the gradation cluster information, a parameter of the gradation is crated for each gradation area Furthermore, using the gradation cluster information, the color are is consolidated, and vector description of a profile of the gradation area is crated on the basis of the consolidated color area

Abstract: A method for processing an image is proposed. The method includes identifying a group of keypoints in an image. The method further comprising calculating for each key-point of the group a corresponding descriptor array comprising a plurality of array elements, each array element having a respective sub-zone of the image in the neighborhood of the key- Lt; RTI ID = 0.0 > histogram. L / RTI > The method includes subdividing the descriptor array into at least two sub-arrays for each key-point of the group, each sub-array comprising a number of elements of the descriptor array, Subdividing the compressed sub-array into sub-arrays, and generating a compressed descriptor comprising a corresponding compressed sub-array for each of the at least two sub-arrays. Each compressed sub-array is obtained by compressing the corresponding sub-arrays of said at least two sub-arrays by vector quantization using respective codebooks. The method further comprises utilizing compressed descriptor arrays of keypoints of the group to analyze the image. Wherein for each key-point in the group, subdividing the descriptor array into at least two sub-arrays is performed based on correlation relationships between the color gradient histograms, and wherein the values of the color gradient histograms It is stored in the elements of each keypoint descriptor array.

Abstract: Moving objects tracked is a challenge in the research field of computer vision, a video moving objects tracking algorithm based on the combination of appearance model is presented in this paper. Gradient information was used separately as well as in conjunction with color information. The objects appearance model was then represented in the form of a histogram which used gradient and color feature spaces, and frame-to-frame tracking is performed using mean-shift program. The experimental result showed that this method could be used to track complex background images and objects of the occlusions movement.

Abstract: The necessity of increasing information density in a given space motivates the use of more colors in color barcodes. A popular system, Microsoft's HCCB technology, uses four or eight colors per patch. This system displays a color palette of four or eight colors in the color barcode to solve the problem with the dependency of the surface color on the illuminant spectrum, viewing parameters, and other sources. Since the displayed colors cannot be used to encode information, this solution comes at the cost of reduced information rate. In this contribution, we introduce a new approach to color barcode decoding that uses 24 colors per patch and requires a small number of reference colors to display in a barcode. Our algorithm builds groups of colors from each color patch and a small number of reference color patches, and models their evolution due to changing illuminant using a linear subspace. Therefore, each group of colors is represented by one such subspace. Our experimental results show that our barcode decoding algorithm achieves higher information rate with a very low probability of decoding error compared to systems that do display a color palette. The computational complexity of our algorithm is relatively low due to searching for the nearest subspace among 24 subspaces only.

Abstract: This paper introduces an automatic color design method that is driven by an importance function of the objects within a volumetric dataset. Our method allows the user to intuitively modify the object classification and the importance distribution function in the 2D rendered image. It automatically computes the transfer function, especially the color distribution, to convey the importance of the objects. In our approach, the importance of an object is represented as the attentiveness of a color. In addition, we preserve the color harmony in the rendered image in order to provide a visually pleasing result. In this paper, we propose a set of computational measurements to compute the color attentiveness and color harmony. Our color assignment algorithm supports arbitrary-dimensional transfer functions and obtains interactive frame rates. Our method involves three color spaces, namely Coloroid system, CIE LChuv, and Adobe RGB color space. It calculates the color attentiveness in CIE LChuv space, and the color harmony in Coloroid system. It, then, assigns the transfer function in a dual space of Adobe RGB space and renders the resulting image in Adobe RGB space. We conducted a detailed user study, which proves that our method successfully conveys the importance distributions. Our contribution in this paper is not only our importance driven approach, but also our computational measurements and our color assignment algorithm. © 2012 Wiley Periodicals, Inc.