Recognition of Human Face using Interconnection Network

Chaddah, Puneet; Yadav, Sangeeta; Ray, Ajoy Kumar

doi:10.1080/03772063.1996.11415932

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…In each filtered image we find the maximum intensity points dynamically and are then marked as fiducial points ( Landmarks on faces) [7]. The main objective in the proposed work is to match the face with the faces in the database [5]. For this we use the concept of complete Fuzzy preference relation.…”

Section: Proposed Workmentioning

confidence: 99%

A Fuzzy Preference Relation Based Method for Face Recognition by Gabor Filters

Biswas¹,

Jha²,

Singh³

2012

IJITCS

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In this paper we have applied Gabor filter for fiducial point localization. After obtaining the fiducial points the number of fiducial points are reduced using a distance formula. The distance of each of this fiducial point is then calculated by the distance formula and stored in the database of the system. The same methodology is also applied on the input face which is to be matched with the faces available in the database. Then a fuzzy preference relation matrix is obtained . the largest eigen value of this matrix is then determined by algebraic method or numerical method depending on the order of the matrix. To apply the numerical method which is more easier for large order matrices we have used the C programming of this method . Once the largest eigen value is determined the corresponding priority vector can easily be obtained from which we can easily match the input face with the database.

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Section: Proposed Workmentioning

confidence: 99%

A Fuzzy Preference Relation Based Method for Face Recognition by Gabor Filters

Biswas¹,

Jha²,

Singh³

2012

IJITCS

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“…After getting these fiducial vectors (Chaddah, 1996), the rotation invariable facial images are grouped under a particular class where it is being trained by an adaptive neural network. In this experiment we have taken 10 facial images of a person from a fixed distance, fixed illumination…”

Section: Fig 1 Face Recognition System By Using a Group Based Adaptiv...mentioning

confidence: 99%

Face Recognition by Bunch Graph Method Using a Group Based Adaptive Tolerant Neural Network

D¹,

Girish²,

Karibasappa³

et al. 2011

BJMCS

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This paper presents a new method for feature extraction from the facial image by using bunch graph method. These extracted geometric features of the face are used subsequently for face recognition by utilizing the group based adaptive neural network. This method is suitable, when the facial images are rotation and translation invariant. Further the technique also free from size invariance of facial image and is capable of identifying the facial images correctly when corrupted with noise/ camouflage. The method shows a result of 97% correct result in facial database of 320 images of 10 classes. The technique can be extended easily to incorporate the rotational invariance of the images.

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A New Method For Face Recognition Using Feature Clustering With Fuzzy Parameters

Biswas¹,

Som²

2013

J. Math. Computer Sci.

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In this paper, we have applied Gabor filter for fiducial point localisation. The fiducial points are represented as trapezoidal fuzzy numbers. These fiducial points are then transformed into crisp numbers. The number of fiducial points are then reduced by using a distance formula. The distance of each of these fiducial points are then stored in the database of the system. The same methodology is applied on the input face which is to be matched with the faces available in the database. Then a fuzzy preference relation matrix is obtained .The largest eigen value of this matrix is then determined. Once the largest eigen value is determined the corresponding priority vector can easily be obtained, from which we can easily match the input face with the database. In the broadest sense we have observed we have used the fuzzy mathematics to counter the impreciseness in facial recognition.

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Recognition of Human Face using Interconnection Network

Cited by 3 publications

References 8 publications

A Fuzzy Preference Relation Based Method for Face Recognition by Gabor Filters

A Fuzzy Preference Relation Based Method for Face Recognition by Gabor Filters

Face Recognition by Bunch Graph Method Using a Group Based Adaptive Tolerant Neural Network

A New Method For Face Recognition Using Feature Clustering With Fuzzy Parameters

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