Fast color-spatial feature based image retrieval methods

Lin, Chuen-Horng; Huang, Der-Chen; Chan, Yung-Kuan; Chen, Kai-Hung; Chang, Yen-Jen

doi:10.1016/j.eswa.2011.03.014

Cited by 48 publications

(24 citation statements)

References 16 publications

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“…Fig. 9 illustrates the comparison of average precision the proposed method with the other methods in [8], [9], and [10]. Vol.…”

Section: Resultsmentioning

confidence: 99%

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An Evolutionary Stochastic Approach for Efficient Image Retrieval using Modified Particle Swarm Optimization

Heidari¹,

Chalechale²

2016

ijacsa

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Abstract-Image retrieval system as a reliable tool can help people in reaching efficient use of digital image accumulation; also finding efficient methods for the retrieval of images is important. Color and texture descriptors are two basic features in image retrieval. In this paper, an approach is employed which represents a composition of color moments and texture features to extract low-level feature of an image. By assigning equal weights for different types of features, we can't obtain good results, but by applying different weights to each feature, this problem is solved. In this work, the weights are improved using a modified Particle Swarm Optimization (PSO) method for increasing average Precision of system. In fact, a novel method based on an evolutionary approach is presented and the motivation of this work is to enhance Precision of the retrieval system with an improved PSO algorithm. The average Precision of presented method using equally weighted features and optimal weighted features is 49.85% and 54.16%, respectively. 4.31% increase in the average Precision achieved by proposed technique can achieve higher recognition accuracy, and the search result is better after using PSO.

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“…Fig. 9 illustrates the comparison of average precision the proposed method with the other methods in [8], [9], and [10]. Vol.…”

Section: Resultsmentioning

confidence: 99%

“…Texture information can be used for recognizing an object [8] and structural methods are used [9] to describe it. The fine feature descriptor is applied to reach the truly matched images [10].…”

Section: Introductionmentioning

confidence: 99%

An Evolutionary Stochastic Approach for Efficient Image Retrieval using Modified Particle Swarm Optimization

Heidari¹,

Chalechale²

2016

ijacsa

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“…The two drawbacks of this approach are firstly, images in the database were manually annoted by annotators and secondly, the retrieval results are poor, because they are similar to the understanding of the query images. The ordinal approach, example, content based image retrieval (CBIR) had been proposed in the early 1990's [4][5][6][7]. This approach is based on retrieving the images by using low level features like colour, shape and texture that can represent an image.…”

Section: Introductionmentioning

confidence: 99%

“…Thus image retrieval becomes an essential topic in pattern recognition domain and image processing. Images can be retrieved in three ways generally: content based, text based and semantic based [1][2][3][4]. Text based retrieval approach is widely used, such as Google and Baidu, and images can retrieved by using keywords that are annotated on images.…”

Section: Introductionmentioning

confidence: 99%

Content Based Image Retrieval Using Gray Level Co-Occurance Matrix with SVD and Local Binary Pattern

Kishore¹,

Kumar²,

Rao³

2016

IJCI

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“…Yildizer et al [34] have proposed an efficient content-based image retrieval using multiple support vector machines ensemble. Lin et al [8] have proposed fast color-spatial feature based image retrieval methods using the the K-means algorithm. The main advantages of the proposed method over the existing methods are given as follows:…”

Section: Introductionmentioning

confidence: 99%

An Expert Local Mesh Correlation Histograms for Biomedical Image Indexing and Retrieval

Vipparthi¹,

Murala²,

Nagar³

et al. 2015

Multimedia Retrieval - Perspectives and Challenges

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Fast color-spatial feature based image retrieval methods

Cited by 48 publications

References 16 publications

An Evolutionary Stochastic Approach for Efficient Image Retrieval using Modified Particle Swarm Optimization

An Evolutionary Stochastic Approach for Efficient Image Retrieval using Modified Particle Swarm Optimization

Content Based Image Retrieval Using Gray Level Co-Occurance Matrix with SVD and Local Binary Pattern

An Expert Local Mesh Correlation Histograms for Biomedical Image Indexing and Retrieval

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