Contemporary integration of content based image retrieval

Shaikh, Riaz Ahmed; Deep, Samundra; Li, Jianping; Kumar, Kamlesh; Khan, Asif; Memon, Imran

doi:10.1109/iccwamtip.2014.7073413

Cited by 10 publications

(2 citation statements)

References 4 publications

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“…Much different from pixel-based image segmentation, object segmentation takes into consideration information including spectrum characteristics, texture, shape, and spatial relation. Other then content-based methods exploiting both visual and textual information from multimedia [37,38], this system is mainly concerned with texture and shape characteristics. Initial segmentation is worth considering in order to extract stable road regions without nonroad pixels.…”

Section: Object Segmentation and Region Growing With Edge Constraintsmentioning

confidence: 99%

Road Extraction from VHR Remote-Sensing Imagery via Object Segmentation Constrained by Gabor Features

Chen

Zhu

Xie

et al. 2018

IJGI

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Automatic road extraction from remote-sensing imagery plays an important role in many applications. However, accurate and efficient extraction from very high-resolution (VHR) images remains difficult because of, for example, increased data size and superfluous details, the spatial and spectral diversity of road targets, disturbances (e.g., vehicles, shadows of trees, and buildings), the necessity of finding weak road edges while avoiding noise, and the fast-acquisition requirement of road information for crisis response. To solve these difficulties, a two-stage method combining edge information and region characteristics is presented. In the first stage, convolutions are executed by applying Gabor wavelets in the best scale to detect Gabor features with location and orientation information. The features are then merged into one response map for connection analysis. In the second stage, highly complete, connected Gabor features are used as edge constraints to facilitate stable object segmentation and limit region growing. Finally, segmented objects are evaluated by some fundamental shape features to eliminate nonroad objects. The results indicate the validity and superiority of the proposed method to efficiently extract accurate road targets from VHR remote-sensing images.

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Section: Object Segmentation and Region Growing With Edge Constraintsmentioning

confidence: 99%

Road Extraction from VHR Remote-Sensing Imagery via Object Segmentation Constrained by Gabor Features

Chen

Zhu

Xie

et al. 2018

IJGI

View full text Add to dashboard Cite

show abstract

“…Shaikh et al [18] proposed a dual layer model SHODHANI, which integrates features and processes and combine neural network approach to sense a specific image and easily retrieved from complex database. Chakraborty et al [19] firstly estimated camera view point and position of the peoples in 3D scene then extraction spatial information from 3D people position.…”

Section: Literature Reviewmentioning

confidence: 99%

Contemporary Layout’s Integration for Geospatial Image Mining

Shaikh¹,

Li²,

Khan³

2016

ijacsa

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Abstract-Image taxonomy and repossession plays a major role in dealing with large multimedia data on the Internet. Social networks, image sharing websites and mobile application require categorizing multimedia items for more efficient search and storage. Therefore, image classification and retrieval methods gained a great importance for researchers and companies. Image classification can be performed in a supervised and semisupervised manner and in order to categorize an unknown image, a statistical model created using relabeled samples is fed with the numerical representation of the visual features of images. Analysis of the keywords surrounding the images or the content of the images alone has not yet achieved results that would allow deriving precise location information to select representative images. Photos that are reliably tagged with labels of place names or areas only cover a small fraction of available images and also remain at a keyword level. State of the art of content based retrieval has been analyzed in earth perception image archives concentrating on complete frameworks indicating guarantee for the operational implementation. The methods are taken into consideration, concentrating specifically on the stages after extraction of primitive features. The solutions conceived for the issues such as synthesis and simplification of features, semantic labeling and indexing are reviewed. The approaches regarding query execution and specification are assessed where conclusions are drawn in the research of earth observation mining.

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GEO matching regions: multiple regions of interests using content based image retrieval based on relative locations

Memon

et al. 2016

Multimed Tools Appl

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Contemporary integration of content based image retrieval

Cited by 10 publications

References 4 publications

Road Extraction from VHR Remote-Sensing Imagery via Object Segmentation Constrained by Gabor Features

Road Extraction from VHR Remote-Sensing Imagery via Object Segmentation Constrained by Gabor Features

Contemporary Layout’s Integration for Geospatial Image Mining

GEO matching regions: multiple regions of interests using content based image retrieval based on relative locations

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