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Content Based Image Retrieval: Survey and Comparison of CBIR System based on Combined Features

Savita Gandhani, Nandini Singhal
2015 International Journal of Signal Processing, Image Processing and Pattern Recognition  
In this paper, performance of various CBIR systems, based on combined feature i.e color texture and shape, are compared.  ...  In image processing, computer vision and pattern recognition, the Image retrieval is a most popular research area.  ...  Basically, the shape contains semantic information of object, and it is different from other elementary visual features, such as color or texture features [3] .  ... 
doi:10.14257/ijsip.2015.8.11.37 fatcat:j7zr22rqdzcfdfbkh5qbaqrdme

Content Based Image Retrieval: Survey and Comparison of CBIR System Based on Combined Features

Savita Gandhani, Nandini Singhal
2015 International Journal of Signal Processing, Image Processing and Pattern Recognition  
In this paper, performance of various CBIR systems, based on combined feature i.e color texture and shape, are compared.  ...  In image processing, computer vision and pattern recognition, the Image retrieval is a most popular research area.  ...  Basically, the shape contains semantic information of object, and it is different from other elementary visual features, such as color or texture features [3] .  ... 
doi:10.14257/ijsip.2015.8.10.18 fatcat:w7i2ghfd4bbq7c34vrx5j57wna

A RESEARCH REVIEW ON RETRIEVAL TECHNIQUES OF DIGITAL IMAGES

Muthuraman M, Dr.Ravichandran S
2017 International Journal of Engineering and Technology  
Image Retrieval (IR) is an exciting and growing research areain multimedia.  ...  IR techniques are required in many fields of digital imaging like Medical Imaging, Remote sensing, Forensic Science, Military and printing.  ...  QBIC uses an R*-tree index to sort images based on significance.  Virage: developed by Virage, retrieves global color, local color, texture and shapes.  ... 
doi:10.21817/ijet/2017/v9i6/170906305 fatcat:eggklh6c5fgchi6bhstte2354m

Content-Based Image Retrieval Features: A Survey

Anum Masood, Muhammad Alyas Shahid, Muhammad Sharif
2018 International journal of advanced networking and applications  
The local shape is more related to the expressing of result instead of the method. Local shape features may be derived from the texture properties and the color derivatives.  ...  Texture features are used in different CBIR systems along with color, shape, geometrical structure and sift features.  ...  Local shape descriptors are related to the geometric details of an image. Local shape features may be derived from the texture properties and the color derivatives.  ... 
doi:10.35444/ijana.2018.100111 fatcat:m7epi7eyinesrlakzafksospnq

Content Based Image Retrieval using Collaborative Color, Texture and Shape Features

2020 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
In this paper, CBIR is implemented using collaboration of color; texture and shape attribute to improve the feature discriminating property.  ...  We have proposed color histogram features for color feature extraction, Local Binary Pattern (LBP) for texture feature extraction, and Histogram of oriented gradients (HOG) for shape attribute extraction  ...  CBIR can be performed using particular combination of the color, texture and shape of the image object, the presence or arrangement of specific types of objects, the view of particular type of event, and  ... 
doi:10.35940/ijitee.b8014.019320 fatcat:4fjja2yiazauvdzm7tf5z6iyeq

Self-supervised Visual Attribute Learning for Fashion Compatibility [article]

Donghyun Kim, Kuniaki Saito, Samarth Mishra, Stan Sclaroff, Kate Saenko, Bryan A Plummer
2021 arXiv   pre-print
However, prior work in SSL focuses on tasks like object recognition or detection, which aim to learn object shapes and assume that the features should be invariant to concepts like colors and textures.  ...  Our tasks include learning to predict color histograms and discriminate shapeless local patches and textures from each instance.  ...  features in colors and textures without encoding shape information.  ... 
arXiv:2008.00348v2 fatcat:n6tpfsjkujcdlmiltmgdvgccge

Illumination color covariant locale-based visual object retrieval

Mark S. Drew, Ze-Nian Li, Zinovi Tauber
2002 Pattern Recognition  
Since the rotation, scale and translation parameters are thus estimated, we can apply an e cient process of texture support and shape veriÿcation.  ...  Making use of feature-consistent locales in an image we develop a scene partition by localization, rather than by image segmentation.  ...  Conclusion This paper presents a color covariant search method by object model using multiple features (color, texture, shape, etc.).  ... 
doi:10.1016/s0031-3203(01)00163-7 fatcat:buygcsuakrhqjhdypcjznibe34

An Analysis of Segmentation Techniques to Identify Herbal Leaves from Complex Background

I. Kiruba Raji, K.K. Thyagharajan
2015 Procedia Computer Science  
In this paper we are examining various object detection techniques for segmenting leaves based on color, shape and texture.  ...  Features like local adaptive mean color, evidence based color model, color histogram techniques are used.  ...  To overcome these drawbacks of global and local adaptive mean color mode and for achieving better results with color images, K-means clustering algorithm is used.  ... 
doi:10.1016/j.procs.2015.04.140 fatcat:pkupsxngvnfcnfll7bb6wkkzve

PARTICLE FILTER-BASED OBJECT TRACKING USING JOINT FEATURES OF COLOR AND LOCAL BINARY PATTERN HISTOGRAM FOURIER

Dewa Made Wiharta
2016 Kursor  
The proposed joint feature is able to capture object with changing shape and has better accuracy than single feature of color or joint color texture from other LBP variants.  ...  In this research, we combine color histogram and texture from Local Binary Pattern Histogram Fourier (LBPHF) operator as feature in object tracking.  ...  Similarly, [7] proposes to combine color and texture extracted by Local Binary Pattern in mean shift tracking, and [12] uses color and texture generated by DWT for tracking object using Gaussian sum  ... 
doi:10.28961/kursor.v8i2.64 fatcat:zbqb2iw6kjapdghz7t4v6mgffu

Separate Channels for Processing Form, Texture, and Color: Evidence from fMRI Adaptation and Visual Object Agnosia

C. Cavina-Pratesi, R.W. Kentridge, C.A. Heywood, A.D. Milner
2010 Cerebral Cortex  
We used stimuli varying in their shape, texture, or color, and tested healthy participants and 2 object-agnosic patients, in both a discrimination task and a functional MR adaptation paradigm.  ...  Previous neuroimaging research suggests that although object shape is analyzed in the lateral occipital cortex, surface properties of objects, such as color and texture, are dealt with in more medial areas  ...  Gouws, and M. Hymers for their assistance with fMRI data collection and to Bob Metcalf for help in hardware development.  ... 
doi:10.1093/cercor/bhp298 pmid:20100900 fatcat:ftbmdktp6vci5ptstsqzfp2yji

Survey on Colour, Texture and Shape Features for Person Re-Identification

E. Poongothai, A. Suruliandi
2016 Indian Journal of Science and Technology  
Findings: From the analysis we found that colour and texture features outperform the shape feature.  ...  Methods/Statistical Analysis: The features for re-identification is categorized into three groups namely colour, texture and shape.  ...  The main objective of this paper is to make a survey on recently used colour, texture and shape features and their characteristics for person re-identification.  ... 
doi:10.17485/ijst/2016/v9i29/93823 fatcat:motusbekajbu5kkeoblbuqrc3e

Identification of paddy leaf diseases based on texture analysis of Blobs and color segmentation

Alex Wenda, Inggih Permana, Yusmar Yusmar, Nunik Noviana
2020 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
This study aims to identification paddy plant diseases based on texture analysis of Blobs and color segmentation. Blobs analysis is used to get the number of objects, area and perimeter.  ...  Color segmentation is used to find out some color parameters of paddy leaf disease such as the color of the lesion boundary, the color of the spot of the lesion, and the color of the paddy leaf lesion.  ...  Object is a lesion on the paddy leaf. Shape texture analysis uses Blobs analysis by calculating the ratio of the boundary box, which is height/width.  ... 
doi:10.12928/telkomnika.v18i4.14614 fatcat:pkqhy4d75zevtmwmprv53hif24

Local Color Voxel and Spatial Pattern for 3D Textured Recognition

Hero Yudo Martono
2017 International Journal on Advanced Science, Engineering and Information Technology  
3D textured retrieval including shape, color dan pattern is still a challenging research.  ...  Some approaches are proposed, but voxel-based approach has not much been made yet, where by using this approach, it still keeps both geometry and texture information.  ...  For the different reason and different use, we study about local extraction on a 3D color voxel to generate local features.  ... 
doi:10.18517/ijaseit.7.2.2173 fatcat:nrd2wggtcbh73lkvqvu6oefxmu

A STUDY AND SURVEY ON CONTENT-BASED IMAGE RETRIEVAL USING LOW LEVEL FEATURES FOR MOBILE DEVICES

Manjusha Y. Patil, Amol B. Kasture
2020 Samvakti Journal of Research in Information Technology  
features like color, texture and shape for efficient and accurate image retrieval on mobile devices.  ...  In Content based Image Retrieval (CBIR), images are retrieved by their visual content such as color, texture and shapes.  ...  Today, CBIR features such as Color, Shape and textures using these fillings we retrieve images from large image scale database.  ... 
doi:10.46402/202007.343.48.255 fatcat:knj6oozskne6dmgzv6s2tnmh2u

A survey on cbir techniques and learning algorithm comparison

2016 International Journal of Latest Trends in Engineering and Technology  
[8] present that CBIR uses visual image contents for example global features-color feature, shape feature, texture feature, and local features-spatial domain present to indicate and image index.  ...  CBIR depends upon visual low-Ievel feature extraction i-e color, texture, shape and spatial layout.  ... 
doi:10.21172/1.81.026 fatcat:jvw72a4pmjhmzogib5gqy7sgqm
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