A new vector space model for image retrieval

Karamti, Hanen; Tmar, Mohamed; Gargouri, Faïez

doi:10.1016/j.procs.2017.08.202

Cited by 4 publications

(10 citation statements)

References 23 publications

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“…Methods for determining the contours of color images [1,[5][6][7][8] provide for the preliminary conversion of a color image into a tonal one. After conversion, in the future, well-known methods for determining the contours of objects on tone images are used.…”

Section: Review Of Problemmentioning

confidence: 99%

“…In [6,7], heterogeneous methods of spatial differentiation are used (Sobel, Prewitt, Roberts, Wallace methods, sequential masking, etc.). The main disadvantages of the methods are the presence of gaps, points, and strokes forming an interfering background, the need to know the initial approximation to the desired boundary, and significant computational costs.…”

Section: Computer Sciencesmentioning

confidence: 99%

“…In well-known works [1,2,5,6,10], various quantitative indicators are used to evaluate the quality of image processing. Such indicators take into account the type of image, the presence or absence of a priori information about objects of interest, etc.…”

Section: Computer Sciencesmentioning

confidence: 99%

“…Machine learning methods are used in computer vision systems, decoding of aerospace images, medicine, bioinformatics, automatic speech recognition, etc. [1,2,5,6].…”

Section: Introductionmentioning

confidence: 99%

“…Existing methods for determining the contours of objects in color images provide for the preliminary conversion of a color image into a tonal image [1,5,6] and the further use of wellknown methods for determining the contours of objects in tone images [1,7,8]. A study of the use of well-known methods for determining the contours of objects in color images indicates the following disadvantages [1,[5][6][7][8]:…”

Section: Introductionmentioning

confidence: 99%

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Development of Methods for Determining the Contours of Objects for a Complex Structured Color Image Based on the Ant Colony Optimization Algorithm

Khudov

Рубан

Makoveichuk

et al. 2020

EUREKA: Physics and Engineering

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A method for determining the contours of objects on complexly structured color images based on the ant colony optimization algorithm is proposed. The method for determining the contours of objects of interest in complexly structured color images based on the ant colony optimization algorithm, unlike the known ones, provides for the following. Color channels are highlighted. In each color channel, a brightness channel is allocated. The contours of objects of interest are determined by the method based on the ant colony optimization algorithm. At the end, the transition back to the original color model (the combination of color channels) is carried out. A typical complex structured color image is processed to determine the contours of objects using the ant colony optimization algorithm. The image is presented in the RGB color space. It is established that objects of interest can be determined on the resulting image. At the same time, the presence of a large number of "garbage" objects on the resulting image is noted. This is a disadvantage of the developed method. A visual comparison of the application of the developed method and the known methods for determining the contours of objects is carried out. It is established that the developed method improves the accuracy of determining the contours of objects. Errors of the first and second kind are chosen as quantitative indicators of the accuracy of determining the contours of objects in a typical complex structured color image. Errors of the first and second kind are determined by the criterion of maximum likelihood, which follows from the generalized criterion of minimum average risk. The errors of the first and second kind are estimated when determining the contours of objects in a typical complex structured color image using known methods and the developed method. The well-known methods are the Canny, k-means (k=2), k-means (k=3), Random forest methods. It is established that when using the developed method based on the ant colony optimization algorithm, the errors in determining the contours of objects are reduced on average by 5-13 %.

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Section: Review Of Problemmentioning

confidence: 99%

Section: Computer Sciencesmentioning

confidence: 99%

Section: Computer Sciencesmentioning

confidence: 99%

“…Machine learning methods are used in computer vision systems, decoding of aerospace images, medicine, bioinformatics, automatic speech recognition, etc. [1,2,5,6].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Development of Methods for Determining the Contours of Objects for a Complex Structured Color Image Based on the Ant Colony Optimization Algorithm

Khudov

Рубан

Makoveichuk

et al. 2020

EUREKA: Physics and Engineering

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Construction of methods for determining the contours of objects on tonal aerospace images based on the ant algorithms

Рубан¹,

Khudov²,

Makoveichuk³

et al. 2019

EEJET

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Performance Evaluation of Information Retrieval System Using Vector Space Model: A Comparative Analysis

Al-rassam,

Hama Saeed Mohammed Amin,

Shaho Faeq

2021

ijci

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The increasing use of the internet has created a vast amount of digital information and it is expanding extremely fast. Therefore, Information retrieval becomes a challenging task to fetch relevant information for users. The aim of this paper was to examine and evaluate the performance of the Information retrieval system through eight experiments to test all the features that can be used in a vector space model. These experiments were compared to show the best and the worst implemented features. The features are represented by applying (tf.idf, stop words, stemming), (tf.idf, No- stop words, stemming), (tf.idf, No- stop words, No-stemming), (tf.idf, stop words, No-stemming), (tf, stop words, stemming), (tf, No- stop words, stemming), (tf, No- stop words, No-stemming), (tf, stop words, No-stemming). Results showed that using stop words, stemming approach, and tf.idf improve the performance of the system. However, when tf was used without using stop words and stemming approaches the performance of the system is declined. In addition, results showed that stop words have a significant effect on the system while the stemming approach has no noticeable effect particularly with tf.

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A new vector space model for image retrieval

Cited by 4 publications

References 23 publications

Development of Methods for Determining the Contours of Objects for a Complex Structured Color Image Based on the Ant Colony Optimization Algorithm

Development of Methods for Determining the Contours of Objects for a Complex Structured Color Image Based on the Ant Colony Optimization Algorithm

Construction of methods for determining the contours of objects on tonal aerospace images based on the ant algorithms

Performance Evaluation of Information Retrieval System Using Vector Space Model: A Comparative Analysis

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