Application of SIFT feature extraction algorithm on the image registration

Liu, Jinxia; Qiu, Yuehong

doi:10.1109/icemi.2011.6037882

Cited by 7 publications

(4 citation statements)

References 7 publications

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“…The SIFT algorith m presented by Lowe [1], is based on multiple scales and spaces, it focuses on transforming an image into a large collection of local features or points of interest [6], each of these is invariant to scale, rotation and a certain degree of illu mination. This algorithm is divided into four sections [1], shown below.…”

Section: IImentioning

confidence: 99%

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A Feature Extraction Using SIFT with a Preprocessing by Adding CLAHE Algorithm to Enhance Image Histograms

Olvera

Zeron

Pedraza-Ortega

et al. 2014

2014 International Conference on Mechatronics, Electronics and Automotive Engineering

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In this paper a novel method is proposed to improve the performance of the S IFT (S cale Invariant Feature Transformation) algorithm in adverse illumination conditions (in an outdoor environment at night), for this research it is proposed to work with CLAHE (Contrast Limited Adaptive Histogram Equalization), adding a preprocessing stage to the traditional methodology of the S IFT algorithm, this will be applied to the building to be found in the scene, i.e., the image pattern.A comparison with different illumination conditions (day, evening and night) will be held to know the response that will have the S IFT algorithm and to identify which moment the algorithm has a better performance.

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Section: IImentioning

confidence: 99%

“…Later will be filtered unstable points with a great answer to the edges, for it will be used a Hessian matrix: (6) If the value of is less than a certain threshold value (TH), it's accepted as a one of the points of interest. However, unstable objects with great response to edges are discarded.…”

Section: B Keypoints Localizationmentioning

confidence: 99%

A Feature Extraction Using SIFT with a Preprocessing by Adding CLAHE Algorithm to Enhance Image Histograms

Olvera

Zeron

Pedraza-Ortega

et al. 2014

2014 International Conference on Mechatronics, Electronics and Automotive Engineering

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“…Its parallel hardware design has a real-time feature extraction process that can meet the needs of real-time applications. Jinxia and Yuehong [16] proposed a technology to improve registration performance through BBF and RANSAC algorithms. The BBF algorithm finds the optimal identity point and eliminates the mismatch of the RANSAC algorithm.…”

Section: Introductionmentioning

confidence: 99%

Hybrid recommendation algorithm of cross-border e-commerce items based on artificial intelligence and multiview collaborative fusion

2021

Neural Comput & Applic

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E-commerce platforms apply recommendation technology to a wide variety of commercial websites to help users quickly find the product they need from a large number of products. At present, recommendation systems have been widely used in large-scale e-commerce websites, and most e-commerce shopping websites attract customers through the image information of goods. In this paper, the research status of content-based image retrieval algorithms is analysed, and how to use image content information to recommend goods is studied. A hierarchical commodity classification and retrieval system are designed. A class decision layer is used to determine the category of commodity images and then precisely retrieve the corresponding category of commodity image features. The corresponding relationship between different commodity visual features is used to recommend commodities, and a matching recommendation algorithm for commodities is proposed. Experiments show that the proposed image content-based recommendation method can coordinate with features, and its recommendation results have high accuracy in practical applications.

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“…A color histogram is a representation of the distribution of colors in an image [13]. For digital images, a color histogram represents the number of pixels that have colors in each of a fixed list of color ranges that span the image"s color space, the set of all possible colors.…”

Section: Color Histogram (Color Detector)mentioning

confidence: 99%

A Review on Image Encryption Technique and to Extract Feature from Image

Singh¹,

Mandoria²

2017

IJCA

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The security of image data from unauthorized users is important hence image encryption play an important role in hiding information. This survey paper measure up the different encryption techniques for securing multimedia data with objective to give complete review on the various encryption techniques. This paper presents a review of survey literature published from 2008 to 2015 in aspect of different image encryption/decryption techniques with tabular form and the algorithms used to extract the features from the images. KeywordsEncryption, feature extraction, color, texture, algorithms.the correlation between image elements was significantly decreased. Results also show that increasing the number of blocks by using smaller block sizes resulted in a lower correlation and higher entropy [1].An Image Encryption Approach Using a Combination of Permutation Technique Followed by Encryption: It is a new permutation technique based on the combination of image permutation and a well known encryption algorithm called RijnDael. The original image was divided into 4×4 pixels blocks, which were repositioned into a permuted image using a permutation process, and then the generated image was encrypted using the RijnDael algorithm [2]. Younes results show that the connection between image elements was significantly decreased by using the combination technique and higher entropy was attained.

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Application of SIFT feature extraction algorithm on the image registration

Cited by 7 publications

References 7 publications

A Feature Extraction Using SIFT with a Preprocessing by Adding CLAHE Algorithm to Enhance Image Histograms

A Feature Extraction Using SIFT with a Preprocessing by Adding CLAHE Algorithm to Enhance Image Histograms

Hybrid recommendation algorithm of cross-border e-commerce items based on artificial intelligence and multiview collaborative fusion

A Review on Image Encryption Technique and to Extract Feature from Image

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