A novel Genetic Algorithms and SURF-Based approach for image retargeting

Oliveira, Saulo A. F.; Neto, Ajalmar R. Rocha; Bezerra, Francisco Nivando

doi:10.1016/j.eswa.2015.09.015

Cited by 11 publications

(6 citation statements)

References 17 publications

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“…The discrete method of content‐aware image resizing is based on the scaling method of SC. This method considers the image as discrete pixels and deletes pixels from the image based on their importance [3, 4]. The Seam Carving ‐ Scaling ‐ Combined optimized Image resizing algorithm (SCSC) algorithm is a discrete method that coherently executes line cropping and uniform scaling to scale an image.…”

Section: Background Studymentioning

confidence: 99%

Structure preservation in content‐aware image retargeting using multi‐operator

Garg

Negi²

2020

IET image process

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Section: Background Studymentioning

confidence: 99%

Structure preservation in content‐aware image retargeting using multi‐operator

Garg

Negi²

2020

IET image process

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“…Both [17] and [18] used the SIFT-based Fisher vector in the process of extracting local feature vectors [21] [22]. By contrast, we use the SURF method [23] [24], which produces fewer local features and outperforms the SIFT method in term of feature extraction processing speed.…”

Section: Related Workmentioning

confidence: 99%

“…SURF algorithm is used in our work [21] [22]. This technique is an innovative descriptor and scale and rotation variant detector that matches or often surpasses the patented SIFT algorithm [23] [24] in terms of computation and comparison as well as robustness, distinctiveness and repeatability.…”

Section: Feature Extractionmentioning

confidence: 99%

EEIRI: Efficient Encrypted Image Retrieval in IoT-Cloud

2019

KSII TIIS

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One of the best means to safeguard the confidentiality, security, and privacy of an image within the IoT-Cloud is through encryption. However, looking through encrypted data is a difficult process. Several techniques for searching encrypted data have been devised, but certain security solutions may not be used in IoT-Cloud because such solutions are not lightweight. We propose a lightweight scheme that can perform a content-based search of encrypted images, namely EEIRI. In this scheme, the images are represented using local features. We develop and validate a secure scheme for measuring the Euclidean distance between two descriptor sets. To improve the search efficiency, we employ the k-means clustering technique to construct a searchable tree-based index. Our index construction process ensures the privacy of the stored data and search requests. When compared with more familiar techniques of searching images over plaintexts, EEIRI is considered to be more efficient, demonstrating a higher search cost of 7% and a decrease in search accuracy of 1.7%. Numerous empirical investigations are carried out in relation to real image collections so as to evidence our work.

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“…In referred study, the optimized design of SURF has been realized by using TSMC 65 nm process. Oliveira et al [5] have presented a new approach to retarget images based on both genetic algorithm and a highperformance scale and rotation-invariant interest point descriptor.…”

Section: Introductionmentioning

confidence: 99%

GA-Based Optimization of SURF Algorithm and Realization Based on Vivado-HLS

Özdemir¹,

Sever²,

Polat³

2019

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The aim of this study is realization of SURF algorithm based on Vivado-HLS tool for FPGA platform. The SURF algorithm is a method which is used in image processing that is not affected by feature changes such as size, color and contrast. Genetic algorithm is used to determine the optimum values of the parameters affecting the success of the SURF algorithm in this work. It has been observed that when the parameter values determined using the optimization algorithm is used, the success rate significantly increases. The proposed method has been tested for character recognition application with fixed font which is independent from rotation and character size. In this work, the tests were carried out with images formed from numbers. Reference and test pictures for each number were created. The test images consist of images of different sizes and rotations. Optimal parameter values were used in HLS after being determined by proposed approach. Using the proposed optimized SURF structure, high success rates were obtained.

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A novel Genetic Algorithms and SURF-Based approach for image retargeting

Cited by 11 publications

References 17 publications

Structure preservation in content‐aware image retargeting using multi‐operator

Structure preservation in content‐aware image retargeting using multi‐operator

EEIRI: Efficient Encrypted Image Retrieval in IoT-Cloud

GA-Based Optimization of SURF Algorithm and Realization Based on Vivado-HLS

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