Color Space Conversion Research Articles

Method of Color Medical Image Enhancement Based on Color Space Conversion

Method of Color Medical Image Enhancement Based on Color Space Conversion

Integration method of 3D MR spectroscopy into treatment planning system for glioblastoma IMRT dose painting with integrated simultaneous boost

BackgroundTo integrate 3D MR spectroscopy imaging (MRSI) in the treatment planning system (TPS) for glioblastoma dose painting to guide simultaneous integrated boost (SIB) in intensity-modulated radiation therapy (IMRT).MethodsFor sixteen glioblastoma patients, we have simulated three types of dosimetry plans, one conventional plan of 60-Gy in 3D conformational radiotherapy (3D-CRT), one 60-Gy plan in IMRT and one 72-Gy plan in SIB-IMRT. All sixteen MRSI metabolic maps were integrated into TPS, using normalization with color-space conversion and threshold-based segmentation. The fusion between the metabolic maps and the planning CT scans were assessed. Dosimetry comparisons were performed between the different plans of 60-Gy 3D-CRT, 60-Gy IMRT and 72-Gy SIB-IMRT, the last plan was targeted on MRSI abnormalities and contrast enhancement (CE).ResultsFusion assessment was performed for 160 transformations. It resulted in maximum differences <1.00 mm for translation parameters and ≤1.15° for rotation. Dosimetry plans of 72-Gy SIB-IMRT and 60-Gy IMRT showed a significantly decreased maximum dose to the brainstem (44.00 and 44.30 vs. 57.01 Gy) and decreased high dose-volumes to normal brain (19 and 20 vs. 23% and 7 and 7 vs. 12%) compared to 60-Gy 3D-CRT (p < 0.05).ConclusionsDelivering standard doses to conventional target and higher doses to new target volumes characterized by MRSI and CE is now possible and does not increase dose to organs at risk. MRSI and CE abnormalities are now integrated for glioblastoma SIB-IMRT, concomitant with temozolomide, in an ongoing multi-institutional phase-III clinical trial. Our method of MR spectroscopy maps integration to TPS is robust and reliable; integration to neuronavigation systems with this method could also improve glioblastoma resection or guide biopsies.

Automation of CMOS technology migration illustrated by RGB to YCrCb analogue converter

AbstractThe paper illustrates a practical example of technology migration applied to the colour space converter realized in CMOS technology. The element has analogue excitation and response signals expressed in current mode. Such converter may be incorporated into an integrated vision sensor for preconditioning acquired image data. The idea of a computer software tool supporting the automated migration and design reuse is presented as the major contribution. The mentioned tools implement the Hooke-Jeeves direct search method for performing the multivariable optimization. Our purpose is to ensure transferring the circuit between usable fabrication technologies and preserving its functional properties. The colour space converter is treated as the case study for performance evaluation of the proposed tool in cooperation with HSPICE simulation software. The original CMOS technology files for Taiwan semiconductor (TSMC) plant were utilized for the research. The automated design migration from 180 nm into 90 nm resulted with obtaining compact IC layout characterized by a smaller area and lower power consumption. The paper is concluded with a brief summary that proves the usability of the proposed tool in designing CMOS cells dedicated for low power image processing.

Separate Color Correction for Tone Compression in HDR Image Rendering

Many High-Dynamic-Range (HDR) rendering techniques have been developed. Of these, the image color appearance model, iCAM, is a typical HDR image rendering algorithm. HDR rendering methods normally require a tone compression process and include many color space transformations from the RGB signal of an input image to the RGB signal of output devices for the realistic depiction of a captured image. The iCAM06, which is a refined iCAM, also contains a tone compression step and several color space conversions for HDR image reproduction. On the other hand, the tone compression and frequent color space changes in the iCAM06 cause color distortion, such as a hue shift and saturation reduction of the output image. To solve these problems, this paper proposes a separate color correction method that has no effect on the output luminance values by controlling only the saturation and hue of the color attributes. The color saturation of the output image was compensated for using the compensation gain and the hue shift was corrected using the rotation matrix. The separate color correction method reduces the existing color changes in iCAM06. The compensation gain and rotation matrix for the color correction were formulated based on the relationship between the input and output tristimulus values through the tone compression. The experimental results show that the revised iCAM06 with the proposed method has better performance than the default iCAM06.

Study on the Model of Chromaticity Closed-Loop Control for Print Online Detection

The print online detection technology contains wide range of content, for instance alignment inspection, defect detection and color detection, among them the color detection is the most difficult. In this paper, IGT printability tester is used to produce different ink film thickness samples of the yellow, magenta, cyan, black and map spot colors brown, blue, green, red, purple and other colors. Based on large number of experiment data collected, though mathematical modeling, data analysis, experimental validation and model updating, a closed-loop control model and techniques based on the chromaticity detection are proposed. By establishing the model of the relationship between the chromaticity value and the ink film thickness, the relationship between the ink film thickness and the ink key opening, the numerical calculation between the chromaticity and the ink key opening is achieved. The basic method of chromaticity closed-loop control is: when printing began, the model calculates the initial ink key opening with the ink preset algorithm, and set the ink key opening. After entering the print state, the model detects the RGB value of print by the machine vision technology, and converts the RGB value to CIE LAB values by color space conversion and gamut mapping. Then the model compares the Lab values with the standard values, determines whether the color-difference overrun. If the color-difference is within the allowable range, the model maintains the original amount of ink and ink key opening. If it exceeds the limit value, the model quickly calculates the deviation of the ink amount, and offers the ink key opening which is corresponding to the adjustment, feedbacks it to the print control center, resulting in the ink key response in order to achieve the real-time adjustment of the print ink amount. Compared with the control method of the ink amount based on density detection, the chromatic detection method is more accurate, and has better application prospects.

Research on Robustness of Color Device Characteristic Methods Based on Artificial Intelligence

The nature of device color characteristic methods is the mutual conversion of device-dependent color space and device-independent color space. This paper does the comparative study on the robustness of some color space conversion methods which are based on fuzzy control, dynamic subspace divided BP neural network identification method, and fuzzy and neural identification method, by defining the robustness of color space conversion model and evaluation method. The result shows that the device color characteristic methods which are based on fuzzy and neural identification method can make the feature of BP neural network combine with fuzzy control to greatly improve the robustness of model.

The Experimental Research on Tiled Multiple Projectors Displaying Based on ICC Mechanism

The research on the color uniformity of the tiled multiple projectors display systems gets more and more attention. In this paper, taking the tiled two-projector display system as a case, the color calibration method based on ICC color management mechanism was proposed and used to achieve the color uniformity the non-overlapping projected region firstly. And the sectoring parabola interpretation algorithm was used to achieve the color uniformity of the overlapping projected region. The research content of this paper includes: ①The ICC profile of the projector based on matrix model was calculated and generated; ②The ICC profile of the projector based on 3-dimensions lookup table model was calculated and generated; ③The color-matching precision of the above two types of ICC profiles were compared by the color space conversion experiment, and the feasibility of color calibration method of the non-overlapping projected region based on ICC mechanism was verified; ④Finally, the feasibility of color calibration method of the overlapping projected region based on sectoring parabola interpretation algorithm was verified by Quest3D development platform.

Image Preprocessing of CMOS Image Acquisition System Based on FPGA

The paper introduces a high-frame-rate and high-resolution image acquisition system with DVI Interface, which uses the CMOS image sensor of 2.3 million pixels as the light-sensitive chip and a high-performance FPGA as the main processor. In order to get better image quality and correct the unrealistic color, the image preprocessing is implemented based on FPGA, including color space conversion and auto white balance. Firstly, RGB color space is conversed to YCbCr color space. Then a novel auto white balance algorithm is proposed to correct the unrealistic color iteratively. The experiment results show that the color space conversion greatly simplifies the design process with four DSP48E units. And the novel auto white balance algorithm improves the precision of channel gains.

A hybrid neural network Imperialist Competitive Algorithm for skin color segmentation

Skin color detection is a popular and useful technique because of its wide range of utilizations both in human computer interaction and content based analysis. Applications such as detecting and tracking of human body parts, face detection and recognition, naked people detection and people retrieval in multimedia databases all benefit from skin detection. Hence finding a proper method for segment the skin-like pixels can solve the presented problems. The Imperialist Competitive Algorithm (ICA) is a new evolutionary algorithm which was recently introduced and has a good performance in some optimization problems. The ICA was inspired by socio-political processes of imperialistic competition of mankind in the real world. In this paper a hybrid ICA-ANN is proposed for solving skin classification. A new algorithm that combines ICA and ANN to solve skin classification has been proposed, and then a hybrid Neural Network (NN)-Imperialist Competitive Algorithm (ICA) is applied to solve the classification problem. In the proposed algorithm, a multi layer perceptron network (MLP) manages the problem’s constraints and an ICA algorithm searches for high quality solutions and minimum cost. The proposed color segmentation algorithm operates directly on RGB color space without the need of color space conversion. Experimental results show that this method can improve the performance of the MLP algorithm significantly.

REAL-TIME VIDEO WATERMARKING FOR COPYRIGHT PROTECTION BASED ON HUMAN PERCEPTION

There is a need for real-time copyright logo insertion in emerging applications, such as Internet protocol television (IPTV). This situation arises in IP-TV and digital TV broadcasting when video residing in a server has to be broadcast by different stations and under different broadcasting rights. Embedded systems that are involved in broadcasting need to have embedded copyright protection. Existing works are targeted towards invisible watermarking, not useful for logo insertion. MPEG-4 is the mainstream exchangeable video format in the Internet today because it has higher and flexible compression rate, lower bit rate, and higher efficiency while superior visual quality.The main steps for MPEG-4 are color space conversion and sampling, DCT and its inverse (IDCT), quantization, zigzag scanning, motion estimation, and entropy coding. In this work a watermarking algorithm that performs the broadcaster's logo insertion as watermark in the DCT domain is been presented. The robustness of DCT watermarking arises from the fact that if an attack tries to remove watermarking at mid frequencies, it will risk degrading the fidelity of the image\video because some perceptive details are at mid frequencies. The suggested methods has implemented in matlab.

VECTORIZATION OF LINEAR FEATURES IN SCANNED TOPOGRAPHIC MAPS USING ADAPTIVE IMAGE SEGMENTATION AND SEQUENTIAL LINE TRACKING

Abstract. Vectorization of cartographic features is a difficult task in geographic information acquisition from topographic maps. This paper presents a semi-automatic approach to linear feature vectorization directly in original scanned colour topographic maps without layer separation. In the approach, a sliding window is added on a user-given linear feature, and the current line in the window is segmented adaptively by using colour space conversion, k-means clustering and directional region growing. A thinning operation is then performed in the window and the line is tracked from the centre to the edge. By moving the window continuously along the line, vectorization is carried out by iterative operations of image segmentation, thinning and line tracking. Experimental results show that linear features in colour topographic maps can be vectorized rapidly and accurately, especially in those maps with forest tints and relief shadings.

Design of a Video Processor Based on FPGA

The design of a kind of video processor with the function of auto-focusing is introduced in this paper. The video processor receives digital 8-bit YCbCr video signal. With a piece of DDR2 SDRAM as frame buffer, the video processor realizes the function of format conversion, frame up-scaling and color space conversion. The paper proposes an improved gray scale differential auto-focus algorithm and calculates the focus value of the current image real-timely. Applying the mountain climbing searching strategy to control the moving of the focus motor, and realize the function of auto-focusing. The whole design is realized in VHDL and verified with Xilinx XUPV5-LX110T FPGA developing board.

Text, photo, and line extraction in scanned documents

We propose a page layout analysis algorithm to classify a scanned document into different regions such as text, photo, or strong lines. The proposed scheme consists of five modules. The first module performs several image preprocessing techniques such as image scaling, filtering, color space conversion, and gamma correction to enhance the scanned image quality and reduce the computation time in later stages. Text detection is applied in the second module wherein wavelet transform and run-length encoding are employed to generate and validate text regions, respectively. The third module uses a Markov random field based block-wise segmentation that employs a basis vector projection technique with maximum a posteriori probability optimization to detect photo regions. In the fourth module, methods for edge detection, edge linking, line-segment fitting, and Hough transform are utilized to detect strong edges and lines. In the last module, the resultant text, photo, and edge maps are combined to generate a page layout map using K-Means clustering. The proposed algorithm has been tested on several hundred documents that contain simple and complex page layout structures and contents such as articles, magazines, business cards, dictionaries, and newsletters, and compared against state-of-the-art page-segmentation techniques with benchmark performance. The results indicate that our methodology achieves an average of ∼ 89% classification accuracy in text, photo, and background regions.

Efficient LUT-Based Truncated Multiplier and Its Application in RGB to YCbCr Color Space Conversion

Efficient LUT-Based Truncated Multiplier and Its Application in RGB to YCbCr Color Space Conversion

An efficient joint implementation of three stages for fast computation of color space conversation in image coding/decoding

This paper proposes an efficient joint implementation algorithm for computing color space conversion, quantization and discrete cosine transform (DCT) in an image coder/decoder. By combining the three stages, the proposed algorithm reduces the operation amount of computing color space conversion considerably. In the case of color sampling 4:4:4, the proposed algorithm reduces the multiplication amount by 40% and the addition amount by 42% for the conversion from RGB to YCbCr in an image coder, and reduces the multiplication amount by 60% and the addition amount by 42% for the conversion from YCbCr to RGB in an image decoder. In the cases of down-sampling 4:2:2 and 4:1:1, there are the similar results. The existing fast methods in the literatures can still be applied together with this proposed algorithm into the implementation of the international image coding standards which use the transform coding technology, such as JPEG, MPEG and H.26X, and raises the image coding/decoding speed efficiently.

Face Recognition Based on Projected Color Space With Lighting Compensation

In this letter, we propose a novel color space conversion method called adaptive projection color space (APCS). This method includes two portions: adaptive singular value decomposition and an inner product conversion algorithm for color images. We employed images from the Color FERET and CMU-PIE databases for training and experiment. The results revealed that the recognition rates from our proposed APCS approach were higher than other color spaces and those of methods proposed in relevant studies.

Evaluation of Huffman and Arithmetic Algorithms for Multimedia Compression Standards

Compression is a technique to reduce the quantity of data without excessively reducing the quality of the multimedia data.The transition and storing of compressed multimedia data is much faster and more efficient than original uncompressed multimedia data. There are various techniques and standards for multimedia data compression, especially for image compression such as the JPEG and JPEG2000 standards. These standards consist of different functions such as color space conversion and entropy coding. Arithmetic and Huffman coding are normally used in the entropy coding phase. In this paper we try to answer the following question. Which entropy coding, arithmetic or Huffman, is more suitable compared to other from the compression ratio, performance, and implementation points of view? We have implemented and tested Huffman and arithmetic algorithms. Our implemented results show that compression ratio of arithmetic coding is better than Huffman coding, while the performance of the Huffman coding is higher than arithmetic coding. In addition, implementation of Huffman coding is much easier than the arithmetic coding.

Analysis and classification for complex scanned documents

Page-layout-classification methodologies aim to extract text and non-textual regions such as graphics, photos, or logos. These techniques have applications in digital document storage and retrieval where efficient memory consumption and quick retrieval are required.1 Such classification algorithms can also be used in the printing industry for selective or enhanced scanning and object-oriented rendering (printing different parts of a document with different resolution depending on the content).2 Additionally, these techniques can be used as an initial step for various applications. These include optical-character recognition (the electronic translation of handwritten or printed text into machine-encoded text) and graphic interpretation (classifying documents—into military, educational, and others—according to the image content).3 In the past two decades, several techniques have focused on identifying text regions in scanned documents.4, 5 In addition, comprehensive algorithms that aim to identify both text and graphic regions have been developed.6, 7 However, these systems are limited to specific documents, such as newsletters or articles, where the background region is assumed white.8, 9 This assumption not only excludes complex backgrounds and colored documents (such as book covers, advertisements, and flyers),10 but also limits practicality and feasibility when applied to non-ideal (complex) documents. We propose a page-layout-segmentation technique to extract text, image, and strong-edge or strong-line regions (actual lines in the document or transition pixels between a picture and text or a picture and background).11 The algorithm consists of four modules: pre-processing stage, text detection, photo detection, and strong-edge or strong-line detection units. We start by applying a pre-processing module that includes image scaling and enhancement, as well as color-space conversion Figure 1. Line detection results for two different documents. (a) Original image, (b) enhanced L* channel of the CIE L*a*b* space, and (c) final segmentation map where strong-edge or strong-line and text regions are colored in yellow and green, respectively.

A target-based color space for sea target detection

Sea target detection is a vital application for military and navigation purposes. A new supervised clustering method based on the combination of the PSO and FCM techniques is presented for the sea target detection problem. The color components of the target and non-target pixels in the RGB color space are used as features to train the classification algorithm. The new classifier is presented in the form of a new color space which we call the Target-based Color Space (TCS); in fact the RGB color space is converted to this new space through a 3×3 matrix. The Particle Swarm Optimization (PSO) algorithm is then used to search for the optimum weights of the conversion matrix which results in a more discriminating clustering space between the target and non-target pixels. In other words, solving the optimization problem, minimization of the objective function of the FCM clustering technique in linear and quadratic transform domain (with a NP-hard problem in quadratic conversion), is done using the PSO algorithm. The main objective of this work is to demonstrate the efficiency of using just color features, as well as color space conversion in the classification domain. Experimental results show the efficiency of new method in finding sea targets in color images.

Implementation of Multiplier less Architectures for Color Space Conversions on FPGA

Implementation of Multiplier less Architectures for Color Space Conversions on FPGA