In this work, we shall present some novel process to measure the similarity between picture fuzzy sets. Firstly, we adopt the concept of intuitionistic fuzzy sets, interval-valued intuitionistic fuzzy sets and picture fuzzy sets. Secondly, we develop some similarity measures between picture fuzzy sets, such as, cosine similarity measure, weighted cosine similarity measure, set-theoretic similar...

We address in this paper automatic face verification from 3D (3-dimensional) facial surface and grey level analysis. 3D acquisition is performed by a structured light system, adapted to face capture and allowing grey level acquisition in alignment. The 3D facial shapes are compared and the residual error after 3D matching is used as a first similarity measure. A second similarity measure is der...

scott and szewczyk in technometrics, 2001, have introduced a similarity measure for twodensities f1 and f2 , by1, 21 21 1 2 2( , ), ,f fsim f ff f f f< >=< >< >wheref1, f2 f1(x, θ1)f2(x, θ2)dx.+∞−∞< >=∫sim(f1, f2) has some appropriate properties that can be suitable measures for the similarity of f1 and f2 .however, due to some restrictions on the value of parameters and the kind of densities, ...

In general, there are two fundamental issues in content-based image retrieval (CBIR): content representation and similarity matching. Once the set of feature vector representing the content of images is determined, the question of how to combine the individual similarities according to each term of the vector to form a global similarity must be addressed. In this paper, the low frequency DCT co...

Recently the entropy-similarity measure has been introduced for the registration of image pairs prior to subtraction in medical imaging e.g. digital subtraction angiography (DSA). The registration is based on motion-vector fields estimated with a template-matching techniques. The entropy is calculated via weighted grey-value histograms of the difference-image template and measures the degree of...

Reliability of similarity measure is a key factor for successful image matching. In this paper, mutual information is introduced to template image matching as a similarity measure. Its ability of adapting to different scene, overcoming the grey reversal, and factors which influence on the successful matching of mutual information method are discussed. These factors include signal-noise ratio, i...

Effective image retrieval by content from database requires that visual image properties are used instead of textual labels to recover pictorial data. Retrieval by image similarity given a template image is particularly challenging. The difficulty is to derive a similarity measure that combines shape, grey level patterns and texture in a way that closely conforms to human perception. In this pa...

in this paper, we present a revised similarity measure based onchen-and-chen's similarity measure for fuzzy risk analysis. the revisedsimilarity measure uses the corrected formulae to calculate the centre ofgravity points, therefore it is more  effective than the chen-and-chen'smethod. the revised similarity measure can overcome the drawbacks of theexisting methods. we have also proposed a new ...

In this paper, 3D voxel-similarity-based (VB) registration algorithms that optimize a feature-space clustering measure are proposed to combine the segmentation and registration process. We present a unifying de nition and a classi cation scheme for existing VB matching criteria and propose a new matching criterion: the entropy of the grey-level scatter-plot. This criterion requires no segmentat...