Color face image enhancement using adaptive singular value decomposition in fourier domain for face recognition

Wang, Jing-Wein; Le, Ngoc Tuyen; Lee, Jiann-Shu; Wang, Chou-Chen

doi:10.1016/j.patcog.2016.03.021

Cited by 41 publications

(19 citation statements)

References 28 publications

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“…where G is the set of the input factors; T is the set of the moments of reading information; Ω is the space of features of recognition; Z is the space of possible EMS of a person; Y is the set of the signals after initial processing of the information; 1…”

Section: Materials and Methods Of The Studymentioning

confidence: 99%

“…The main drawback of the known methods of intelligent analysis is the use of distance measures of proximity [1,2] or similarity [3,4], which in practice decreases the probability of making correct diagnostic decisions considering emotional and mental state (EMS) of a person. In the works of [5,6], the methods for evaluating EMS of a person with the use of his halftone raster face images are considered.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

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Information synthesis of adaptive system for visual diagnostics of emotional and mental state of a person

Dovbysh

Shelehov

Prylepa

et al. 2016

EEJET

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Section: Materials and Methods Of The Studymentioning

confidence: 99%

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Information synthesis of adaptive system for visual diagnostics of emotional and mental state of a person

Dovbysh

Shelehov

Prylepa

et al. 2016

EEJET

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“…For color image enhancement, many researchers have tried to reduce the effect of illumination on the image. Recently, some researchers were successful in applying singular value decomposition (SVD) for color face image enhancement [19][20][21][22][23]. However, these methods are useful for natural light sources, and not suitable for ski goggles defect color images taken under custom light sources.…”

Section: Defect Image Enhancementmentioning

confidence: 99%

Novel Framework Based on HOSVD for Ski Goggles Defect Detection and Classification

Wang

et al. 2019

Sensors

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No matter your experience level or budget, there is a great ski goggle waiting to be found.Goggles are an essential part of skiing or snowboarding gear to protect your eyes from harsh environmental elements and injury. In the ski goggles manufacturing industry, defects, especially on the lens surface, are unavoidable. However, defect detection and classification by visual inspection in the manufacturing process is very difficult. To overcome this problem, a novel framework based on machine vision is presented, named as the ski goggles lens defect detection, with five high-resolution cameras and custom-made lighting field to achieve a high-quality ski goggles lens image. Next, the defects on the lens of ski goggles are detected by using parallel projection in opposite directions based on adaptive energy analysis. Before being put into the classification system, the defect images are enhanced by an adaptive method based on the high-order singular value decomposition (HOSVD). Finally, dust and five types of defect images are classified into six types, i.e., dust, spotlight (type 1, type 2, type 3), string, and watermark, by using the developed classification algorithm. The defect detection and classification results of the ski goggles lens are compared to the standard quality of the manufacturer. Experiments using 120 ski goggles lens samples collected from the largest manufacturer in Taiwan are conducted to validate the performance of the proposed framework. The accurate defect detection rate is 100% and the classification accuracy rate is 99.3%, while the total running time is short. The results demonstrate that the proposed method is sound and useful for ski goggles lens inspection in industries.

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“…These topics have been used extensively in the real world, for example, used for CCTV, criminal investigations, access control, content annotations within the website environment, etc. [1]. The rapid development of modern society has made more stringent requirements regarding the speed, accuracy and security of identity identification [1,2].…”

Section: Introductionmentioning

confidence: 99%

“…[1]. The rapid development of modern society has made more stringent requirements regarding the speed, accuracy and security of identity identification [1,2]. A Rapid biometric technology development makes it all possible.…”

Section: Introductionmentioning

confidence: 99%

Enhancement Image Intensity of HSV Color Space

2019

IJRTE

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One of factor that affects technology in face detecting or recognizing is illumination. Poor lighting can cause difficulty to the system to recognize face. Although it is over exposure or under exposure. By doing color image processing, it supports the system to detect face in a poor lighting condition. This research used lighting intensity normalization method to increase face detection performance. This method can normalize the light intensity especially on the face lighting. We normalize the light intensity through HSV color space. HSV color space has saturation which is amount of light in the image. The method proceed saturation in image to increase face detection performance. Total number of faces we had tested is 286 faces, the system detect 243 faces before intensity normalization proceed. Whereas, after normalization process, it detects more faces which is 279 faces. As we can see, the percentage improvement before to after intensity normalization is 84.97% to 97.55%. This is 12.58% improvement. We can say this method helps face detection to increase it performance.

show abstract

Color face image enhancement using adaptive singular value decomposition in fourier domain for face recognition

Cited by 41 publications

References 28 publications

Information synthesis of adaptive system for visual diagnostics of emotional and mental state of a person

Information synthesis of adaptive system for visual diagnostics of emotional and mental state of a person

Novel Framework Based on HOSVD for Ski Goggles Defect Detection and Classification

Enhancement Image Intensity of HSV Color Space

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