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A Statistical image Retrieval Method using Color Invariant

A Statistical Image Retrieval Method using Color Invariant

引用

ieee International symposium on computational intelligence in Robotics and Automation

作者： Jin, Cheng Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai 200240 Peoples R China

ISBN: (纸本)9781424448081

Content based image retrieval is an essential task in many image processing applications, among which, color based methods have been receiving constant attentions in past years, because color information is a discriminative descriptor for image retrieval, especially in case of large database. A limitation of previous color based methods is their unsuitability for retrieving similar scenes under varying lighting conditions as color is sensitive to illuminations. Besides image descriptors of some existing methods are with large dimensionality and thus computational expensive. As betterment, an adaptive method is proposed in this paper, which integrates the color invariant with some spatial information of images. Different from previous work, the number of states during the quantization of the color space is not manually determined. Instead, it depends on the context of the image itself, using an adaptive clustering technique: Firstly, feature map consisting of color invariants is established for images. Secondly, the Markov chain model is employed to capture the image both color and spatial information. Thirdly, an image descriptor is computed for each image, not under the frame of the entire fixed color space. To practice our method, similar images are retrieved with a similarity measure based on a two-stage weighted distance. Experiments show that, this method has improved simplicity and compactness without the lost of efficiency and robustness.

关键词： Color

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NSST Based MRI-PET/SPECT Color image Fusion Using Local Features Fuzzy Rules and NSML in YIQ Space 19

NSST Based MRI-PET/SPECT Color Image Fusion Using Local Feat...

引用

19th ieee International symposium on signal processing and Information Technology (ISSPIT)

作者： Ullah, Hikmat Zhao, Yaqin Wu, Longwen Abdalla, Fakheraldin Y. O. Mkindu, Hassan Harbin Inst Technol Sch Elect & Informat Engn Harbin 1500001 Peoples R China

ISBN: (纸本)9781728153414

An improved algorithm for the fusion of anatomical structural MRI (magnetic resonance imaging) and metabolic functional PET (positron emission tomography) or SPECT (single photon emission computed tomography) images is proposed here. First, if any of the source image is in RGB format, it is converted to YIQ color space. Then by taking full advantage of non-subsampled shearlet transform (NSST), both the input images (channel-Y and/or gray-scale) are decomposed into one low frequency subbands (LFS) and several high frequency subbands (HFS). Second, local spatial frequency (SF) and region energy (RE) based fuzzy pixel-rules are applied for the fusion of LFS. Where, the fused HFS coefficient is directly selected by computing and comparing novel sum-modified-Laplacian (NSML) of every HFS, to extract maximum and more useful information. Finally, the required fused image is achieved by inversed NSST and inversed YIQ transform. Experimental results obtained shows that the algorithm significantly achieved maximum feature information from the source images, enhance visual quality and contrast of the fused image, and decrease computational task compared to other state-of-art proposed methods.

关键词： MRI-PET and MRI-SPECT fusion Local-features Fuzzy-rules NSML NSST YIQ

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A Multi-target Edge Service Approach to Real-time image Object Detection 13

A Multi-target Edge Service Approach to Real-time Image Obje...

引用

13th International symposium on computational intelligence and Design (ISCID)

作者： Xin, Tinglin Li, Shuo Zhao, Ting Xia, Weishang Zhao, Lijiao State Grid Jibei Informat & Telecommun Co Beijing 100054 Peoples R China Global Energy Interconnect Res Inst Co Ltd Beijing 102200 Peoples R China

ISBN: (纸本)9781728184463

The networked devices over the IoT environments have accumulated a large volume of data, and therefore it becomes challenging for many typical surveillance applications to handle and analyze these massive real-time data. In this paper, we propose a multi-target approach to real-time object detection for surveillance applications that can be used as an edge service for handling and analyzing the real-time massive data acquired by a huge number of terminal devices. A lightweight multi-layered Convolutional Neural Network based on Darnet-53 structure is adopted to learn the multi-target features in training dataset for classifying and detecting image objects in unseen image instances, which is. A pre-processing approach including image screening, image enhancement and manual category annotation is presented for building the training dataset of surveillance applications. At last, extensive experiments were made to validate the effectiveness and efficiency of handling and analyzing the real-time massive data based on the proposed approach.

关键词： Edge computing edge service surveilance applications multi-target object detection

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Subjective assessment of super-resolution 4K video using paired comparison

Subjective assessment of super-resolution 4K video using pai...

引用

International symposium on Intelligent signal processing and Communication Systems (ISPACS)

作者： Sugie, Masaki Gohshi, Seiichi Takeshita, Hirohisa Mori, Chinatsu Kogakuin Univ Dept Informat Tokyo Japan

ISBN: (纸本)9781479961207

4K television (TV) sets are available in the retail market and some are advertised as featuring a super-resolution (SR) function. In particular, most rely on super-resolution image reconstruction (SRR) to provide high-resolution images. Recently, another SR technology that uses nonlinear signal processing (NLSP) and can work in real time has been proposed. A visual performance of the technology needs to be demonstrated subjectively because the performance of the video equipment is determined subjectively by the end user. The subjective performance of these two SR functions has not been verified. Here, subjective assessments comparing SRR and NLSP and a simple extension by the Lanczos filter (without SR) were conducted. 4K video equipment and 4K experimental videos were used. The assessments combined Scheffe's paired comparison test and BT. 500, the International Telecommunication Union-Radiocommunication Sector's methodology for the subjective assessment of the quality of TV pictures. The assessment results were statistically analyzed, and the results indicated that NLSP demonstrated superior resolution.

关键词： high definition television image reconstruction image resolution video signal processing 4K television sets International Telecommunication Union-Radiocommunication Sector Lanczos filter Scheffe paired comparison test nonlinear signal processing super-resolution 4K video super-resolution function super-resolution image reconstruction video equipment HDTV image quality image resolution Observers signal resolution Video equipment video equipment high-definition television image resolution signal resolution Video signal processing image reconstruction Paired Comparisons image quality Observers Television super-resolution SAVANNAH RIVER OPERATIONS OFFICE Strontium

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Edge saliency based on Biological inspiration for object edge extraction under low illumination 11

Edge saliency based on Biological inspiration for object edg...

引用

11th International symposium on computational intelligence and Design (ISCID)

作者： Deng, Qicao Zhang, Liping Dou, Yiwen Wu, Jincenzi Liu, Tao AnHui Polytechn Univ Sch Mech & Automot Engn Wuhu Peoples R China AnHui Polytechn Univ Sch Comp & Informat Wuhu Peoples R China Deakin Univ Fac Sci Engn & Built Environm Geelong Vic Australia

ISBN: (纸本)9781538685273

Objects edge extraction under low illumination image is helpful to enhance the scotopic vision of human visual system. At present, the traditional edge detection algorithm can not find the important edge information under the low illumination image directly. Due to tackle this problem, an optimized the visual saliency model by using the biological heuristic intelligent algorithm is proposed. It is convenient to obtain edge information of low illuminance image. First of all, after obtaining low illumination image, the visual focus is extracted from optimized visual saliency model at three channel and multi-scale level. Then those edge saliency focuses are determined by normalization and merging strategy. In this way, it lays the foundation for the posterior procedures of visual processing. Experimental results show that the proposed algorithm can accurately locate and extract the edge of the objects under normal illumination and low illumination, and it also has the characteristics of high noise resistance.

关键词： Low Illumination image Edge Saliency Firefly Population Entropy

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Automotive Scenarios for Trajectory Tracking using Machine Learning Techniques and image processing 17

Automotive Scenarios for Trajectory Tracking using Machine L...

引用

17th ieee International symposium on Applied computational intelligence and Informatics, SACI 2023

作者： Moga, Delia Filip, Ioan Politehnica University of Timisoara Department of Automation and Applied Informatics Timisoara Romania

ISBN: (纸本)9798350321104

This paper presents a study on using innovative machine learning techniques that can be applied in automotive traffic scenarios to increase a vehicle's level of autonomy. The overtaking traffic scenario is treated for predicting the vehicle trajectory when overtaking another vehicle and the data is obtained by image processing using a video camera. Two different methods are compared, first by using classic tracking methods and a Kalman filter (as an adaptive filter) and second by using a machine learning technique - Support Vector Machine. The present article uses as inputs the data received from the camera and focuses on tracking selected objects and estimating their position using mainly image processing in automotive scenarios. The main purpose of this work is to experiment and compare different tracking modes to determine those that have the best performances in terms of runtime, memory usage and prediction accuracy. © 2023 ieee.

关键词： Support vector machines

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A computational signal processing system for correlated digital interferometry

A computational signal processing system for correlated digi...

引用

2005 ieee International 48th Midwest symposium on Circuits and Systems, MWSCAS 2005

作者： Villamizar-Morales, Jorge Bautista-Rozo, Lola X. Rodriguez, Domingo A. Automated Information Processing Laboratory Electrical and Computer Engineering Department University of Puerto Rico at Mayaguez Mayaguez PR 00681-9042

This work deals with the development of a computational signal algebra framework for the modeling and simulation of digital image interferometry processing applications, exploiting the rapid prototyping capabilities o... 详细信息

ISBN: (纸本)0780391977

关键词： signal processing

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A Framework for image Classification for an Efficient Dictionary Based Face Recognition System

A Framework for Image Classification for an Efficient Dictio...

引用

ieee International Conference on computational intelligence and Computing Research (ICCIC)

作者： Shahidhabanu, S. Maheswari, N. Geethalakshmi, M. Rajalakshmi Engn Coll Madras Tamil Nadu India VIT Univ Madras Tamil Nadu India VIT Univ SCSE Madras Tamil Nadu India

ISBN: (纸本)9781479915941;9781479915958

The digital multimedia image processing and its functionality of Face recognition have become more flexible. In a variety of digital forensic applications such as source identification, content analysis and authentication, it is necessary to recognize the source with training set. The proposed red length based image classification algorithm is to perform face recognition based on class specific dictionaries and to train the samples from / to each class. The class specific dictionaries are formed with some fixed number of color components. Then compares the test image with the threshold specific class and extract the minimal training set stored in the dictionary. The time taken for the image comparison leads to efficient dictionary based facial recognition which can be then used as proof of evidence towards image forensics.

关键词： image classification Face recognition image forensics

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Electroencephalographic Method Using Fast Fourier Transform Overlap processing for Recognition of Right- or Left-handed Elbow Flexion Motor imagery

Electroencephalographic Method Using Fast Fourier Transform ...

引用

ieee symposium on computational intelligence in Brain Computer Interfaces (CIBCI)

作者： Hiroyasu, Tomoyuki Ohkubo, Yuuki Yamamoto, Utako Doshisha Univ Kyoto 1-3 Tatara Miyakodani Kyotanabe Kyoto 6100394 Japan Doshisha Univ Grad Sch Kyoto Kyotanabe Kyoto 6100394 Japan

ISBN: (纸本)9781479945436

Recently, systems using motor imagery (MI) have been developed as practical examples of brain-computer interface (BCI). Electroencephalography (EEG) was used to generate an electroencephalogram of elbow flexion. In addition, a method was proposed to extract the feature values that would enable the recognition right- or left-handed elbow flexion MI. In the proposed method, fast Fourier transform overlap processing was used to determine the time period required to extract feature values. In this study, the following two experiments were performed. 1) the recognition of right- or left-handed elbow flexion by analyzing only the MI time period and 2) recognition of the right- or left-handed when the MI time period was presumed. In the first experiment, right- or left-handed elbow flexion MI was processed for 20 subjects using support vector machine and the proposed method was used to extract the feature values. In the second experiment, the presumed MI time was determined using the channels in which the highest accuracy was obtained in the first experiment, and then, right- or left-handed recognition was processed for the time period presumed. In the first experiment, the recognition accuracy of the proposed method was superior to that of the previous method in 15 of 20 the subjects. In the second experiment, the mean accuracy was 7.2%. Therefore, the recognition accuracy can be improved by improving the MI detection method.

关键词： biomechanics electroencephalography fast Fourier transforms feature extraction image recognition medical image processing support vector machines BCI EEG brain-computer interface electroencephalographic method fast Fourier transform overlap processing feature extration left-handed elbow flexion motor imagery recognition right-handed elbow flexion motor imagery recognition support vector machine time period Accuracy Bandwidth Elbow Electroencephalography Feature extraction Rhythm Scalp Electroencephalography Support Vector Network Feature extraction Fast Fourier transform elbow flexion Brain-Computer Interfaces Medical image processing image recognition time periods Rhythms Scalp Recognition (Psychology) Elbow Bandwidth Biomechanics

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Double Linear Correlation using DCT and Its Application to Forward and Reverse Matching

Double Linear Correlation using DCT and Its Application to F...

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8th International symposium on image and signal processing and Analysis (ISPA)

作者： Ito, Izumi Egiazarian, Karen Tokyo Inst Technol Tokyo 1528551 Japan Tampere Univ Technol Dept Signal Proc Tampere Finland

ISBN: (纸本)9789531841948;9789531841870

We propose a method of double linear correlation, which enables simultaneous calculation of the linear correlation between a sequence and a template and of the linear correlation between the sequence and the reversed template. Using the symmetric property of the discrete cosine transform (DCT) basis, we need to neither expand sequences symmetrically nor reverse the template. Proper zero-padding in the spatial domain before and after the sequences is considered to isolate the two linear correlations. The proposed method requires DCT types 1 and 2. The computational complexity of the proposed method is lower than that using fast Fourier transform.

关键词： correlation methods discrete cosine transforms pattern matching

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