On the use of hash functions for defect detection in textures for in-camera web inspection systems

Baykal, Ibrahim Cem; Muscedere, Roberto; Jullien, G.A.

doi:10.1109/iscas.2002.1010791

Cited by 19 publications

(14 citation statements)

References 4 publications

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“…The most common patterned textures for investigation were lace [16,17,42,43] and Jacquard fabrics [20,44,[129][130][131][132][133][134]. The methods used could be broadly classified as template-matching approach, and statistical & spectral approach, which are termed hybrid approach.…”

Section: Methods For Other Wallpaper Groups (Hybrid Approach)mentioning

confidence: 99%

“…Hash function method, utilizing the offset properties between defect-free and template patterned textures, was a 1D approach and sensitive to small changes in pattern. Four types of Hash function detected defects from simple to complex textures in [130,135]. Previously, an image block densitometrical profile [136], equivalent to the checksum Hash function in [130,135], was proposed.…”

Section: Statistical and Spectral Approachmentioning

confidence: 99%

“…Four types of Hash function detected defects from simple to complex textures in [130,135]. Previously, an image block densitometrical profile [136], equivalent to the checksum Hash function in [130,135], was proposed. No precise detection result in [130,135,136] was given.…”

Section: Statistical and Spectral Approachmentioning

confidence: 99%

“…Previously, an image block densitometrical profile [136], equivalent to the checksum Hash function in [130,135], was proposed. No precise detection result in [130,135,136] was given. Test of the Hash function method evaluated in [44] was poor.…”

Section: Statistical and Spectral Approachmentioning

confidence: 99%

See 3 more Smart Citations

Automated fabric defect detection—A review

Ngan

Pang

Yung

2011

Image and Vision Computing

431

190

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Section: Methods For Other Wallpaper Groups (Hybrid Approach)mentioning

confidence: 99%

Section: Statistical and Spectral Approachmentioning

confidence: 99%

Section: Statistical and Spectral Approachmentioning

confidence: 99%

Section: Statistical and Spectral Approachmentioning

confidence: 99%

See 2 more Smart Citations

Automated fabric defect detection—A review

Ngan

Pang

Yung

2011

Image and Vision Computing

431

190

View full text Add to dashboard Cite

“…It distinguishes between interesting (salient) motion (e.g., a person) and uninteresting motion (e.g., swaying branches). Another technique introduced in [8], [9] is a line-scan technique to build image signature to detect the defects.…”

Section: Introductionmentioning

confidence: 99%

Event Detection by Spatio-Temporal Indexing of Video Clips

Du¹,

Rahman²,

Sharmeen³

et al. 2014

IJCTE

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Abstract-With the continuous recording of video data in current surveillance systems, it is almost impossible to quickly identify frames where events of interest did occur within a camera scene. This paper presents the concept of Spatio-temporal Indexing, which is a novel video indexing and retrieval technique that can be used for event detection. Spatio-temporal Indexing allows the users to rapidly retrieve the video clips that contain events of interest from a given video library. The proposed indexing technique analyzes the video and stores the Spatio-temporal Indexes that will be further processed to retrieve video clips queried by users. The proposed technique was tested on hours of video recordings. The results obtained provide 99.9% accuracy for event detection and retrieval. The average processing time is 3 seconds to create index for 10 minutes of videousing Intel i5-2400 processor.Index Terms-Incident investigation, video indexing, video summarization, video retrieval.

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On the Use of Hash Functions as Preprocessing Algorithms to Detect Defects on Repeating Definite Textures

Baykal

Jullien

2006

Machine Vision and Applications

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On the use of hash functions for defect detection in textures for in-camera web inspection systems

Cited by 19 publications

References 4 publications

Automated fabric defect detection—A review

Automated fabric defect detection—A review

Event Detection by Spatio-Temporal Indexing of Video Clips

On the Use of Hash Functions as Preprocessing Algorithms to Detect Defects on Repeating Definite Textures

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