Search results for: color SIFT.

Authors: Wei-Jong Yang, Wei-Hau Du, Pau-Choo Chang, Jar-Ferr Yang, Pi-Hsia Hung

Abstract:

The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an important feature for visual thing recognition. With color-based SIFT features and SVM, we can discard unreliable matching pairs and increase the robustness of matching tasks. The experimental results show that the proposed object recognition system with color-assistant SIFT SVM classifier achieves higher recognition rate than that with the traditional gray SIFT and SVM classification in various situations.

Keywords: Color moments, visual thing recognition system, SIFT, color SIFT.

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Authors: Qiu Chen, Feifei Lee, Koji Kotani, Tadahiro Ohmi

Abstract:

In this paper, we present local image descriptor using VQ-SIFT for more effective and efficient image retrieval. Instead of SIFT's weighted orientation histograms, we apply vector quantization (VQ) histogram as an alternate representation for SIFT features. Experimental results show that SIFT features using VQ-based local descriptors can achieve better image retrieval accuracy than the conventional algorithm while the computational cost is significantly reduced.

Keywords: SIFT feature, Vector quantization histogram, Localdescriptor, Image retrieval.

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Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim

Abstract:

All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.

Keywords: Currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features.

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Authors: O. Abusaeeda, J. P. O Evans, D. Downes

Abstract:

We demonstrate the synthesis of intermediary views within a sequence of color encoded, materials discriminating, X-ray images that exhibit animated depth in a visual display. During the image acquisition process, the requirement for a linear X-ray detector array is replaced by synthetic image. Scale Invariant Feature Transform, SIFT, in combination with material segmented morphing is employed to produce synthetic imagery. A quantitative analysis of the feature matching performance of the SIFT is presented along with a comparative study of the synthetic imagery. We show that the total number of matches produced by SIFT reduces as the angular separation between the generating views increases. This effect is accompanied by an increase in the total number of synthetic pixel errors. The trends observed are obtained from 15 different luggage items. This programme of research is in collaboration with the UK Home Office and the US Dept. of Homeland Security.

Keywords: X-ray, kinetic depth, view synthesis, KDE

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Authors: Mingling Zheng, Zhenlong Song, Ke Xu, Hengzhu Liu

Abstract:

Scale Invariant Feature Transform (SIFT) has been widely applied, but extracting SIFT feature is complicated and time-consuming. In this paper, to meet the demand of the real-time applications, SIFT is parallelized and optimized on cluster system, which is named pSIFT. Redundancy storage and communication are used for boundary data to improve the performance, and before representation of feature descriptor, data reallocation is adopted to keep load balance in pSIFT. Experimental results show that pSIFT achieves good speedup and scalability.

Keywords: cluster, image matching, parallelization and optimization, SIFT.

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Authors: Siew-Li Ching, Maziani Sabudin

Abstract:

In this paper, we study on color transformation method on website images for the color blind. The most common category of color blindness is red-green color blindness which is viewed as beige color. By transforming the colors of the images, the color blind can improve their color visibility. They can have a better view when browsing through the websites. To transform colors on the website images, we study on two algorithms which are the conversion techniques from RGB color space to HSV color space and self-organizing color transformation. The comparative study focuses on criteria based on the ease of use, quality, accuracy and efficiency. The outcome of the study leads to enhancement of website images to meet the color blinds- vision requirements in perceiving image detailed.

Keywords: Color blind, color transformation, HSV (Hue, Saturation, Value), RGB (Red, Green, Blue).

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Authors: Xu Guoliang, Tan Qingping

Abstract:

Color printing proceeds with multiple halftone separations overlay. Because of separation overlay misalignment in printing, the percentage of different primary color combination may vary and it will result in color shift. In traditional printing procedure with AM halftone, every separation has different screening angle to make the superposition pattern in a random style, which will reduce the color shift. To evaluate the color shift of printing with hybrid halftoning, we simulate printing procedure with halftone images overlay and calculate the color difference between expected color and color in different overlay misalignment configurations. The color difference for hybrid halftone and AM halftone is very close. So the color shift for hybrid halftone is acceptable with current color printing procedure.

Keywords: color printing, AM halftone, Hybrid halftone, misalignment, color shift, Neugebauer Color Equation

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Authors: P. Phokharatkul, S. Chaisriya, S. Somkuarnpanit, S. Phaiboon, C. Kimpan

Abstract:

This paper proposes a new method for image searches and image indexing in databases with a color temperature histogram. The color temperature histogram can be used for performance improvement of content–based image retrieval by using a combination of color temperature and histogram. The color temperature histogram can be represented by a range of 46 colors. That is more than the color histogram and the dominant color temperature. Moreover, with our method the colors that have the same color temperature can be separated while the dominant color temperature can not. The results showed that the color temperature histogram retrieved an accurate image more often than the dominant color temperature method or color histogram method. This also took less time so the color temperature can be used for indexing and searching for images.

Keywords: Color temperature histogram, color temperature, animage retrieval and content-based image retrieval.

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Authors: Rinaldo Christian Tanumara, Ming Xie, Chi Kit Au

Abstract:

Human perceives color in categories, which may be identified using color name such as red, blue, etc. The categorization is unique for each human being. However despite the individual differences, the categorization is shared among members in society. This allows communication among them, especially when using color name. Sociable robot, to live coexist with human and become part of human society, must also have the shared color categorization, which can be achieved through learning. Many works have been done to enable computer, as brain of robot, to learn color categorization. Most of them rely on modeling of human color perception and mathematical complexities. Differently, in this work, the computer learns color categorization through interaction with humans. This work aims at developing the innate ability of the computer to learn the human-like color categorization. It focuses on the representation of color categorization and how it is built and developed without much mathematical complexity.

Keywords: Color categorization, color learning, machinelearning, color naming.

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Authors: Oh-Yeol Kwon, Sung-Il Chien

Abstract:

A conventional image posterization method occasionally fails to preserve the shape and color of objects due to the uneffective color reduction. This paper proposes a new image posterizartion method by using modified color quantization for preserving the shape and color of objects and color contrast enhancement for improving lightness contrast and saturation. Experiment results show that our proposed method can provide visually more satisfactory posterization result than that of the conventional method.

Keywords: Color contrast enhancement, color quantization, color segmentation, image posterization

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Authors: Rinaldo Christian Tanumara, Ming Xie

Abstract:

Color categorization is shared among members in a society. This allows communication of color, especially when using natural language such as English. Hence sociable robot, to live coexist with human in human society, must also have the shared color categorization. To achieve this, many works have been done relying on modeling of human color perception and mathematical complexities. In contrast, in this work, the computer as brain of the robot learns color categorization through interaction with humans without much mathematical complexities.

Keywords: Color categorization, color learning, machinelearning.

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Authors: Katsuhiro Narikiyo, Shota Hashikawa

Abstract:

This paper proposes a way of removing noises and reducing the number of colors contained in a JPEG image. Main purpose of this project is to convert color images to monochrome images for the color-blind. We treat the crispy color images like the Tokyo subway map. Each color in the image has an important information. But for the color blinds, similar colors cannot be distinguished. If we can convert those colors to different gray values, they can distinguish them. Therefore we try to convert color images to monochrome images.

Keywords: Color-blind, JPEG, Monochrome image, Denoise.

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Authors: Katsuhiro Narikiyo, Naoto Kobayakawa

Abstract:

We proposes a way of removing noises and reducing the number of colors contained in a JPEG image. Main purpose of this project is to convert color images to monochrome images for the color blinds. We treat the crispy color images like the Tokyo subway map. Each color in the image has an important information. But for the color blinds, similar colors cannot be distinguished. If we can convert those colors to different gray values, they can distinguish them.

Keywords: Image processing, Color blind, JPEG

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Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

Abstract:

Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: Color space, neural network, random forest, skin detection, statistical feature.

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Authors: Suwit Sadsunk

Abstract:

The study is about the designed and decorative fabric printing that derived from the Five-color porcelain (Benjarong). The researcher examined the pattern and creativity of the decorative design of the Five-color porcelain (Benjarong) by the artists in order to apply for contemporary arts so that young generation will acknowledge the importance of the Five-color porcelain (Benjarong). The research methodology is both quantitative and qualitative. The researcher conducted an in-depth interview with the operator of five-color porcelain (Benjarong) at Ampawa, Samutsongkram. The information from the interview can be useful and implemented for designing the fabric patterns. The researcher found that there were many formats and designs of the Five-color porcelain (Benjarong) from the past to the present. Its unique design can be applied for the fabric patterns and ready-to-wear clothes properly. After advertising and showing the work of the Five-color porcelain (Benjarong) publicly, there were more young people interested in the Five-color porcelain (Benjarong) than expected which exceeded the objective with positive attitudes towards the Five-color porcelain (Benjarong).

Keywords: Decorative fabric printing, Five-color porcelain (Benjarong).

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Authors: Makoto Hasegawa, Seika Tokumitsu

Abstract:

Spectra of light beams emitted from white-color LED torches are different from those of conventional electric torches. In order to confirm if white-color LED torches can be used as light sources for popular sunset color demonstrations in spite of such differences, spectra of travelled light beams and scattered light beams with each of a white-color LED torch (composed of a blue LED and yellow-color fluorescent material) and a conventional electric torch as a light source were measured and compared with each other in a 50 cm-long water tank for sunset color demonstration experiments. Suspension liquid was prepared from acryl-emulsion and tap-water in the water tank, and light beams from the white-color LED torch or the conventional electric torch were allowed to travel in this suspension liquid. Sunset-like color was actually observed when the white-color LED torch was used as the light source in sunset color demonstrations. However, the observed colors when viewed with naked eye look slightly different from those obtainable with the conventional electric torch. At the same time, with the white-color LED, changes in colors in short to middle wavelength regions were recognized with careful observations. From those results, white-color LED torches are confirmed to be applicable as light sources in sunset color demonstrations, although certain attentions have to be paid. Further advanced classes will be successfully performed with white-color LED torches as light sources.

Keywords: Blue sky demonstration, sunset color demonstration, white LED torch.

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Authors: Khalid Salhi, El Miloud Jaara, Mohammed Talibi Alaoui

Abstract:

In this paper, we present a neural approach for unsupervised natural color-texture image segmentation, which is based on both Kohonen maps and mathematical morphology, using a combination of the texture and the image color information of the image, namely, the fractal features based on fractal dimension are selected to present the information texture, and the color features presented in RGB color space. These features are then used to train the network Kohonen, which will be represented by the underlying probability density function, the segmentation of this map is made by morphological watershed transformation. The performance of our color-texture segmentation approach is compared first, to color-based methods or texture-based methods only, and then to k-means method.

Keywords: Segmentation, color-texture, neural networks, fractal, watershed.

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Authors: Juan F. Gutierrez, Jesus M. Quintero, Diego Sandoval

Abstract:

An important feature of Lighting Emitting Diodes (LED) technology is the fast on-off commutation. This fact allows data transmission using modulation formats such as On-Off Keying (OOK) and Color Shift Keying (CSK). Since, CSK based on three color bands uses red, green, and blue monochromatic LED (RGB-LED) to define a pattern of chromaticities; this type of CSK provides poor color quality on the illuminated area. In this work, we present the design and implementation of a VLC system using RGB-based CSK with 16, 8, and 4 color points, mixing with a steady baseline of a phosphor white-LED, to improve the color quality of the LED-Fixture. The experimental system was assessed in terms of the Symbol Error Rate (SER) and the Color Rendering Index (CRI). Good color quality performance of the LED-Fixture was obtained with an acceptable SER. We describe the laboratory setup used to characterize and calibrate an LED-Fixture.

Keywords: Color rendering index, symbol error rate, color shift keying, visible light communications.

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Authors: Kazuko Sakamoto

Abstract:

Recently, the design is becoming important in product development. The technology which is a strong point of Japan is immediately caught up by the foreign countries, and the price competition begins. Therefore companies tend to plan differentiation of products by the design or a color. The purpose of my work was to consider the optimal color for using by product development. We needed to clarify the thing leading to color preference for this purpose. Two kinds of investigations were made. By the first investigation, we found out that a geographical factor difference existed in color preference. Then, investigation which regarded the difference as latitude was conducted. However, the result expected from the difference in latitude was not obtained. It seems that it is necessary to set up difference of latitude a little more greatly, or to reexamine by other geographical factors.

Keywords: Color preference, product color, difference of latitude, design marketing, international comparison.

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Authors: António J. R. Neves, Rui Garcia, Paulo Dias, Alina Trifan

Abstract:

With the aging of the world population and the continuous growth in technology, service robots are more and more explored nowadays as alternatives to healthcare givers or personal assistants for the elderly or disabled people. Any service robot should be capable of interacting with the human companion, receive commands, navigate through the environment, either known or unknown, and recognize objects. This paper proposes an approach for object recognition based on the use of depth information and color images for a service robot. We present a study on two of the most used methods for object detection, where 3D data is used to detect the position of objects to classify that are found on horizontal surfaces. Since most of the objects of interest accessible for service robots are on these surfaces, the proposed 3D segmentation reduces the processing time and simplifies the scene for object recognition. The first approach for object recognition is based on color histograms, while the second is based on the use of the SIFT and SURF feature descriptors. We present comparative experimental results obtained with a real service robot.

Keywords: Service Robot, Object Recognition, 3D Sensors, Plane Segmentation.

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Authors: Rodrigo Montufar-Chaveznava

Abstract:

The colors of the human skin represent a special category of colors, because they are distinctive from the colors of other natural objects. This category is found as a cluster in color spaces, and the skin color variations between people are mostly due to differences in the intensity. Besides, the face detection based on skin color detection is a faster method as compared to other techniques. In this work, we present a system to track faces by carrying out skin color detection in four different color spaces: HSI, YCbCr, YES and RGB. Once some skin color regions have been detected for each color space, we label each and get some characteristics such as size and position. We are supposing that a face is located in one the detected regions. Next, we compare and employ a polling strategy between labeled regions to determine the final region where the face effectively has been detected and located.

Keywords: Tracking, face detection, image processing, colorspaces.

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Authors: Fattah Alizadeh, Saeed Nalousi, Chiman Savari

Abstract:

Because of increasing demands for security in today-s society and also due to paying much more attention to machine vision, biometric researches, pattern recognition and data retrieval in color images, face detection has got more application. In this article we present a scientific approach for modeling human skin color, and also offer an algorithm that tries to detect faces within color images by combination of skin features and determined threshold in the model. Proposed model is based on statistical data in different color spaces. Offered algorithm, using some specified color threshold, first, divides image pixels into two groups: skin pixel group and non-skin pixel group and then based on some geometric features of face decides which area belongs to face. Two main results that we received from this research are as follow: first, proposed model can be applied easily on different databases and color spaces to establish proper threshold. Second, our algorithm can adapt itself with runtime condition and its results demonstrate desirable progress in comparison with similar cases.

Keywords: face detection, skin color modeling, color, colorfulimages, face recognition.

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Authors: M. Lakshmi, J. Senthil Kumar

Abstract:

Digital cameras to reduce cost, use an image sensor to capture color images. Color Filter Array (CFA) in digital cameras permits only one of the three primary (red-green-blue) colors to be sensed in a pixel and interpolates the two missing components through a method named demosaicking. Captured data is interpolated into a full color image and compressed in applications. Color interpolation before compression leads to data redundancy. This paper proposes a new Vector Quantization (VQ) technique to construct a VQ codebook with Differential Evolution (DE) Algorithm. The new technique is compared to conventional Linde- Buzo-Gray (LBG) method.

Keywords: Color Filter Array (CFA), Biorthogonal Wavelet, Vector Quantization (VQ), Differential Evolution (DE).

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Authors: Jong-hwa Kim, Mu-wook Pyeon, Yang-dam Eo, Ill-woong Jang

Abstract:

Construction of geo-spatial information recently tends to develop as multi-dimensional geo-spatial information. People constructing spatial information is also expanding its area to the general public from some experts. As well as, studies are in progress using a variety of devices, with the aim of near real-time update. In this paper, getting the stereo images using GoPro device used widely also to the general public as well as experts. And correcting the distortion of the images, then by using SIFT, DLT, is acquired the point clouds. It presented a possibility that on the basis of this experiment, using a video device that is readily available in real life, to create a real-time digital map.

Keywords: GoPro, SIFT, DLT, Point Clouds.

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Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

Abstract:

This paper presents an unsupervised color image segmentation method. It is based on a hierarchical analysis of 2-D histogram in RGB color space. This histogram minimizes storage space of images and thus facilitates the operations between them. The improved segmentation approach shows a better identification of objects in a color image and, at the same time, the system is fast.

Keywords: Image segmentation, hierarchical analysis, 2-D histogram, Classification.

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Authors: Dr. H. B. Kekre, Sudeep D. Thepade

Abstract:

Panoramic view generation has always offered novel and distinct challenges in the field of image processing. Panoramic view generation is nothing but construction of bigger view mosaic image from set of partial images of the desired view. The paper presents a solution to one of the problems of image seascape formation where some of the partial images are color and others are grayscale. The simplest solution could be to convert all image parts into grayscale images and fusing them to get grayscale image panorama. But in the multihued world, obtaining the colored seascape will always be preferred. This could be achieved by picking colors from the color parts and squirting them in grayscale parts of the seascape. So firstly the grayscale image parts should be colored with help of color image parts and then these parts should be fused to construct the seascape image. The problem of coloring grayscale images has no exact solution. In the proposed technique of panoramic view generation, the job of transferring color traits from reference color image to grayscale image is done by palette based method. In this technique, the color palette is prepared using pixel windows of some degrees taken from color image parts. Then the grayscale image part is divided into pixel windows with same degrees. For every window of grayscale image part the palette is searched and equivalent color values are found, which could be used to color grayscale window. For palette preparation we have used RGB color space and Kekre-s LUV color space. Kekre-s LUV color space gives better quality of coloring. The searching time through color palette is improved over the exhaustive search using Kekre-s fast search technique. After coloring the grayscale image pieces the next job is fusion of all these pieces to obtain panoramic view. For similarity estimation between partial images correlation coefficient is used.

Keywords: Panoramic View, Similarity Estimate, Color Transfer, Color Palette, Kekre's Fast Search, Kekre's LUV

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Authors: Ardhendu Behera, Denis Lalanne, Rolf Ingold

Abstract:

This paper proposes a method, combining color and layout features, for identifying documents captured from low-resolution handheld devices. On one hand, the document image color density surface is estimated and represented with an equivalent ellipse and on the other hand, the document shallow layout structure is computed and hierarchically represented. Our identification method first uses the color information in the documents in order to focus the search space on documents having a similar color distribution, and finally selects the document having the most similar layout structure in the remaining of the search space.

Keywords: Document color modeling, document visualsignature, kernel density estimation, document identification.

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Authors: Hamed Qazanfari, Hamid Hassanpour, Kazem Qazanfari

Abstract:

In this paper, a method is provided for content-based image retrieval. Content-based image retrieval system searches query an image based on its visual content in an image database to retrieve similar images. In this paper, with the aim of simulating the human visual system sensitivity to image's edges and color features, the concept of color difference histogram (CDH) is used. CDH includes the perceptually color difference between two neighboring pixels with regard to colors and edge orientations. Since the HSV color space is close to the human visual system, the CDH is calculated in this color space. In addition, to improve the color features, the color histogram in HSV color space is also used as a feature. Among the extracted features, efficient features are selected using entropy and correlation criteria. The final features extract the content of images most efficiently. The proposed method has been evaluated on three standard databases Corel 5k, Corel 10k and UKBench. Experimental results show that the accuracy of the proposed image retrieval method is significantly improved compared to the recently developed methods.

Keywords: Content-based image retrieval, color difference histogram, efficient features selection, entropy, correlation.

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Authors: S. Piramu Kailasam

Abstract:

This study is expected to compress true color image with compression algorithms in color spaces to provide high compression rates. The need of high compression ratio is to improve storage space. Alternative aim is to rank compression algorithms in a suitable color space. The dataset is sequence of true color images with size 128 x 128. HAAR Wavelet is one of the famous wavelet transforms, has great potential and maintains image quality of color images. HAAR wavelet Transform using Set Partitioning in Hierarchical Trees (SPIHT) algorithm with different color spaces framework is applied to compress sequence of images with angles. Embedded Zerotrees of Wavelet (EZW) is a powerful standard method to sequence data. Hence the proposed compression frame work of HAAR wavelet, xyz color space, morphological gradient and applied image with EZW compression, obtained improvement to other methods, in terms of Compression Ratio, Mean Square Error, Peak Signal Noise Ratio and Bits Per Pixel quality measures.

Keywords: Color Spaces, HAAR Wavelet, Morphological Gradient, Embedded Zerotrees Wavelet Compression.

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Authors: M. V. Sudhamani, C. R. Venugopal

Abstract:

Content-based Image Retrieval (CBIR) aims at searching image databases for specific images that are similar to a given query image based on matching of features derived from the image content. This paper focuses on a low-dimensional color based indexing technique for achieving efficient and effective retrieval performance. In our approach, the color features are extracted using the mean shift algorithm, a robust clustering technique. Then the cluster (region) mode is used as representative of the image in 3-D color space. The feature descriptor consists of the representative color of a region and is indexed using a spatial indexing method that uses *R -tree thus avoiding the high-dimensional indexing problems associated with the traditional color histogram. Alternatively, the images in the database are clustered based on region feature similarity using Euclidian distance. Only representative (centroids) features of these clusters are indexed using *R -tree thus improving the efficiency. For similarity retrieval, each representative color in the query image or region is used independently to find regions containing that color. The results of these methods are compared. A JAVA based query engine supporting query-by- example is built to retrieve images by color.

Keywords: Content-based, indexing, cluster, region.

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