A novel method for resemblance images using near fuzzy set

Ghozzi, Yosr; Baklouti, Nesrine; Alimi, Adel M.

doi:10.1109/aiccsa.2016.7945749

Cited by 2 publications

(1 citation statement)

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“…Thus, the recovery task can be considered as the similarity between sets of objects based on their descriptions. A tolerance measure of nearness (similarity) TNM was introduced in [12], which was applied to problems of image analysis and CBIR [13]- [17]. It was proven that TNM may perform as better than other measures in many real-world applications.…”

Section: Introductionmentioning

confidence: 99%

Interval Type-2 Beta Fuzzy Near Sets Approach to Content-Based Image Retrieval

Ghozzi

Baklouti

Hagras

et al. 2022

IEEE Trans. Fuzzy Syst.

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In computer-based search systems, similarity plays a key role in replicating the human search process which underlies many natural abilities, such as image recovery, language comprehension, decision making, or pattern recognition. The search for images consists in establishing a correspondence between the available images and those sought by the user, by measuring the similarity between the images. In fact, image search per content is generally based on the similarity between the visual characteristics of the images. The distance function used to evaluate the similarity between images depends notonly on the criteria of the search but also on the representation of the characteristics of the image. This is the main idea of a contentbased image retrieval (CBIR) system. In this article, we first constructed type-2 beta fuzzy membership of descriptor vectors to help manage inaccuracy and uncertainty of the characteristics extracted from the feature of images. Subsequently, the retrieved images are ranked according to the novel similarity measure, which is noted type-2 fuzzy nearness measure (IT2FNM). By analogy to Type-2 Fuzzy Logic, and motivated by a near sets theory, we advanced a new fuzzy similarity measure (FSM) noted as interval type-2 fuzzy nearness measure (IT-2 FNM). Then, we proposed three new IT-2 FSMs and provided mathematical justification to demonstrate that the proposed FSMs satisfy proximity properties (i.e. reflexivity, transitivity, symmetry, and overlapping). The experimental results generated using three image databases show consistent and significant results.

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Section: Introductionmentioning

confidence: 99%