A decisive content based image retrieval approach for feature fusion in visual and textual images

Unar, Salahuddin; Wang, Xingyuan; Wang, Chunpeng; Wang, Yu

doi:10.1016/j.knosys.2019.05.001

Cited by 51 publications

(24 citation statements)

References 51 publications

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“…e algorithm in this study fuses the feature vectors by matching technology, monitors three-dimensional fusion target in the target area of basketball video, reconstructs the video that is not in the target area [15][16][17], and takes resolution reconstruction and spatial exchange matching of target data in the target area of basketball video. e calculation formula is as follows:…”

Section: Acquisition Of Target Data In Basketball Videomentioning

confidence: 99%

Target Tracking Algorithm of Basketball Video Based on Improved Grey Neural Network

Wang

Huang

2021

Scientific Programming

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Considering the limitation of tracking range on sports video target tracking in basketball games, there are some problems, such as poor tracking effect, low accuracy, low anti-interference ability, and being time-consuming. Therefore, this study proposes a target tracking algorithm of basketball video based on improved grey neural network. According to the pixel grey difference of the target image in basketball video, this study applies the adaptive threshold algorithm in order to segment the target image of basketball video and obtain the target area of basketball video. This algorithm can normalize the grey level of the target area, build the generating sequence of the target area, and collect the target data of the basketball video. It obtains the feature output matrix of basketball video target based on the geometric dispersion of the target image and extracts the key feature points of basketball video target by single frame visual difference analysis. In addition, it makes use of the improved grey neural network to track and locate the feature points of basketball video target and reconstruct the basketball video target image with superresolution to realize basketball video target tracking. The experimental results show that the proposed algorithm has good target tracking effect of basketball video, can effectively improve the target tracking accuracy and anti-interference ability, and can shorten the target tracking time.

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Section: Acquisition Of Target Data In Basketball Videomentioning

confidence: 99%

Target Tracking Algorithm of Basketball Video Based on Improved Grey Neural Network

Wang

Huang

2021

Scientific Programming

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“…e dual hesitant fuzzy direction line element characteristics of T I were extracted (5). while i < N do//traversal database (6).…”

Section: Retrieval Performance Analysismentioning

confidence: 99%

“…e theoretical basis of image retrieval of Chinese characters in ancient books is content-based image retrieval [1,2]. e key link is feature extraction and matching, that is, color, texture, shape, and other features [3][4][5] or their fusion features [6] are extracted through mathematical descriptions, and similarity calculation is conducted based on image features to identify images that are similar. Traditional Chinese character feature extraction methods mainly adopt structural features [7] and statistical features [8].…”

Section: Introductionmentioning

confidence: 99%

Ancient Chinese Character Image Retrieval Based on Dual Hesitant Fuzzy Sets

Yang

Tian

2021

Scientific Programming

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The complex and changeable structures of ancient Chinese characters result in the decreasing accuracy of their image retrieval. To resolve this problem, a new retrieval method based on dual hesitant fuzzy sets is proposed. Dual hesitation fuzzy sets that can express uncertain information more comprehensively are employed in the feature extraction process of directional line elements. The multiattribute evaluation index of adjacent grids for the current grid and its corresponding membership and nonmembership functions are established, and the weight of each attribute is calculated by the dual hesitation fuzzy entropy, such that the proposed features can fully reflect the topological structure of ancient Chinese characters. Using the dual hesitation fuzzy correlation coefficient to measure the similarity between the ancient Chinese character images to be retrieved and the candidate images, the retrieval of ancient Chinese character images is realized. Experiments show that when the t0hreshold value of the correlation coefficient is 0.9, the average retrieval accuracy is 90.4%.

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“…Work [25] presents a decisive content based ImR approach for feature fusion in visual and textual images. In [30] a system is proposed to combine textual and visual statistics in a single index vector for content-based retrieval. Work [29] presents a system based on content-based and develops its own ontology module, it contributes to significantly increase the relevance of retrieval results, by enhancing the ranking of images.…”

Section: Image Retrieval Techniquesmentioning

confidence: 99%

Graph-Based Image Retrieval: State of the Art

Belahyane

Mammass

Abioui

et al. 2020

Lecture Notes in Computer Science

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The paper deals with the problem of semantic Image Retrieval. Indeed, the image has recently gained popularity in several domains such as medical domain, marketing, etc. Image plays a very vital role in documentation. However, finding visual and relevant information in an image is a huge task for Image Retrieval community and a very discussed issue in digital image processing. In fact, image can be extracted from a big collection of images, in the purpose of responding to user's need. Image Retrieval processes based on classical techniques may not be sufficient to user. For several years, great efforts have been devoted to integrate semantic aspect, in order to enhance relevance of the result and ensure high-level content consideration in image. This paper presents a state of the art of Image Retrieval approaches using graph theory due to the growing interest given to graphs in terms of performance, representation and its ability to ingrate semantic aspect. We review a number of recently available graph-based approaches in Image Retrieval aiming to determine factors adding semantic aspect in Image Retrieval system.

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A decisive content based image retrieval approach for feature fusion in visual and textual images

Cited by 51 publications

References 51 publications

Target Tracking Algorithm of Basketball Video Based on Improved Grey Neural Network

Target Tracking Algorithm of Basketball Video Based on Improved Grey Neural Network

Ancient Chinese Character Image Retrieval Based on Dual Hesitant Fuzzy Sets

Graph-Based Image Retrieval: State of the Art

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