Classification of fragments of objects by the Fourier masks pattern recognition system

Barajas-García, Carolina; Solorza-Calderón, Selene; Álvarez-Borrego, Josué

doi:10.1016/j.optcom.2016.01.059

Cited by 14 publications

(3 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When such problems are solved for face recognition [1,2], identification of objects by their text, graphic or video images [3][4][5][6][7][8], for medical [9,10] or technical diagnostics [11,12], the named optimization criterion is a priority. Its achieving depends on the selected method of classification, caused often by specific subject area of the studies Thus, for instance, nonparametric methods are mainly used in pharmacological applications [13] while in the tasks of trouble-shooting in the series-connected units of chemical engineering systems they use parametric methods [14].…”

Section: Introductionmentioning

confidence: 99%

Localization of vectors–patterns in the problems of parametric classification with the purpose of increasing its accuracy

Aouati¹

2016

EEJET

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Localization of vectors–patterns in the problems of parametric classification with the purpose of increasing its accuracy

Aouati¹

2016

EEJET

View full text Add to dashboard Cite

“…, cos , sin c c pixel [15,16]. Taking a cross-section of those concentric cylinders, the binary rings masks associated to the given sub-image are built.…”

Section: Mathematical Analysismentioning

confidence: 99%

Identification of melanoma cells: a method based in mean variance of signatures via spectral densities

Guerra-Rosas

Álvarez-Borrego

Angulo‐Molina

2017

Biomed. Opt. Express

Self Cite

View full text Add to dashboard Cite

Noninvasive approaches," J. Am. Acad. Dermatol. 72(6), 929-941 (2015). 12. J. March, M. Hand, A. Truong, and D. Grossman, "Practical application of new technologies for melanoma diagnosis: Part II. Molecular approaches," J. Am. Acad. Dermatol. 72(6), 943-958 (2015). 13. E. Guerra-Rosas and J. Álvarez-Borrego, "Methodology for diagnosing of skin cancer on images of dermatologic spots by spectral analysis," Biomed.

show abstract

“…SIFT is widely used, because of the innovative idea of using key points to represent the relevant information, allowing to work with images containing several objects, scenarios and even fragments of objects, unlike other patterns recognition systems as Principal Component Analysis (PCA) [3], or the binary mask system based on one-dimensional signatures [4,5]. However, SIFT have several disadvantages, the computation time is considerable and has low performance with images that present few amount of noise or inhomogeneous illumination.…”

Section: Introductionmentioning

confidence: 99%

Wavelet Local Feature (WLF) Pattern Recognition System

Barajas-García¹,

Solorza-Calderón²

2018

RCS

Self Cite

View full text Add to dashboard Cite

In this paper is presented a pattern recognition methodology based on local feature extraction. The purpose of this system is to identify and locate, in three different scale pyramids, key points that represent relevant information of the image; this information is stored in a descriptor which is used to compares the key points of two images and know if they have similar information, or if they are the same images. This methodology uses the Haar wavelet transform to generate the three scale pyramids. This transform is used because it has several properties, such as noise elimination, multi-resolution analysis, and detection of diagonal, horizontal and vertical edges. The performance of this system was tasted using images with different scales and comparing the results with the Scale Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF) methodologies. The WLF system showed to has the highest percentage of correct point-matching.

show abstract

Classification of fragments of objects by the Fourier masks pattern recognition system

Cited by 14 publications

References 16 publications

Localization of vectors–patterns in the problems of parametric classification with the purpose of increasing its accuracy

Localization of vectors–patterns in the problems of parametric classification with the purpose of increasing its accuracy

Identification of melanoma cells: a method based in mean variance of signatures via spectral densities

Wavelet Local Feature (WLF) Pattern Recognition System

Contact Info

Product

Resources

About