Speechreading: an overview of image processing, feature extraction, sensory integration and pattern recognition techniques

2002 ◽  
Author(s):  
D.G. Stork ◽  
M.E. Hennecke
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Feature Extraction ◽  
Sensory Integration ◽  
Pattern Recognition Techniques

scholarly journals Computer analysis of cervical cells. Automatic feature extraction and classification.

1978 ◽  
Vol 26 (11) ◽  
pp. 1000-1017 ◽  
Author(s):  
J Holmquist ◽  
E Bengtsson ◽  
O Eriksson ◽  
B Nordin ◽  
B Stenkvist
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Feature Extraction ◽  
Computer Analysis ◽  
Single Cells ◽  
Pattern Recognition Techniques ◽  
Automatic Feature Extraction ◽  
Computerized Image Processing ◽  
Atypical Cells ◽  
Cervical Cells

A prescreening instrument for cervical smears using computerized image processing and pattern recognition techniques requires that single cells in the specimen can be automatically isolated and analyzed. This paper describes a dual wavelength method for automatic isolation of the cytoplasm and nuclei of cells. Density-oriented, shape-oriented and texture-oriented parameters were calculated and evaluated for more than 600 cells. It is shown that the computer can be taught to distinguish between normal and atypical cells with an accuracy of ca. 97%, while human classification reproducibility is ca. 95%. In addition, an attempt to assign a measure of atypia to individual cells is described.

Feature Extraction

2017 ◽  
pp. 48-105
Author(s):  
Anindita Das Bhattacharjee
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Pattern Recognition ◽  
Feature Extraction ◽  
Extraction Process ◽  
Measured Data ◽  
Data Set ◽  
Content Domain ◽  
Accessibility Problem ◽  
The Common

Accessibility problem is relevant for audiovisual information, where enormous data has to be explored and processed. Most of the solutions for this specific type of problems point towards a regular need of extracting applicable information features for a given content domain. And feature extraction process deals with two complicated tasks first deciding and then extracting. There are certain properties expected from good features-Repeatability, Distinctiveness, Locality, Quantity, Accuracy, Efficiency, and Invariance. Different feature extraction techniques are described. The chapter concentrates of taking a survey on the topic of Feature extraction and Image formation. Here both image and video are considered to have their feature extracted. In machine learning, pattern recognition and in image processing has significant contribution. The feature extraction is one of the common mechanisms involved in these two techniques. Extracting feature initiates from an initial data set of measured data and constructs derived informative values which are non redundant in nature.

Inspection of tire tread defects using image processing and pattern recognition techniques

1993 ◽  
Author(s):  
Penny Chen ◽  
Gary D. Shubinsky ◽  
Kwan-Hwa Jan ◽  
Chien-An Chen ◽  
Oliver Sidla ◽  
...  
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Pattern Recognition Techniques

scholarly journals Review of local binary pattern operators in image feature extraction

2020 ◽  
Vol 19 (1) ◽  
pp. 23
Author(s):  
Shihab Hamad Khaleefah ◽  
Salama A. Mostafa ◽  
Aida Mustapha ◽  
Mohammad Faidzul Nasrudin
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Feature Extraction ◽  
Local Binary Pattern ◽  
Image Feature ◽  
Image Feature Extraction ◽  
Classification Image ◽  
Current Trends ◽  
Segmentation Pattern ◽  
Information Image

<span>With the substantial expansion of image information, image processing and computer vision have significant roles in several applications, including image classification, image segmentation, pattern recognition, and image retrieval. An important feature that has been applied in many image applications is texture. Texture is the characteristic of a set of pixels that form an image. Therefore, analyzing texture has a significant impact on segmenting an image or detecting important portions of an image. This paper provides a review on LBP and its modifications. The aim of this review is to show the current trends for using, modifying and adapting LBP in the domain of image processing.</span>

Automatic Detection of the Cracks on the Concrete Railway Sleepers

2019 ◽  
Vol 33 (09) ◽  
pp. 1955010
Author(s):  
Seyed Amir Hossein Tabatabaei ◽  
Ahmad Delforouzi ◽  
Muhammad Hassan Khan ◽  
Tim Wesener ◽  
Marcin Grzegorzek
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Intelligent Systems ◽  
Crack Detection ◽  
Image Data ◽  
Experimental Comparison ◽  
Pattern Recognition Techniques ◽  
Comparison Results ◽  
Recognition Systems ◽  
Computer Recognition

A vision-based method for detecting the cracks in the concrete sleepers of the railway tracks will be introduced in this paper. The method is able to detect and partially classify the cracks of the concrete sleepers in two successive steps based on the image processing and pattern recognition techniques. The method has been implemented on the acquired image data frames followed by the analysis, experimental, comparison results and evaluation. The presented results are reasonable which indicates the goodness of the introduced method. The preliminary results of this work have been presented in [A. Delforouzi, A. H. Tabatabaei, M. H. Khan and M. Grzegorzek, A vision-based method for automatic crack detection in railway sleepers, in Kurzynski, M., Wozniak, M., Burduk, R. (eds.), Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017, Polanica Zdroj, Poland. CORES 2017. Advances in Intelligent Systems and Computing, Vol. 578 (Springer, Cham, 2018), pp. 130–139, doi: 10.1007/978-3-319-59162-9_14].

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