HUMAN FACE IMAGE PROCESSING TECHNIQUES

2001 ◽  
Vol 01 (02) ◽  
pp. 197-215 ◽  
Author(s):  
HONG YAN
Keyword(s):  
Image Processing ◽  
Research Work ◽  
Facial Feature ◽  
Face Image ◽  
Computer Algorithms ◽  
Human Face ◽  
Feature Location ◽  
Image Processing Techniques ◽  
Face Image Processing ◽  
Processing Techniques

Human face image processing techniques have many applications, such as in security operations, entertainment, medical imaging and telecommunications. In this paper, we provide an overview of existing computer algorithms for face detection and facial feature location, face recognition, image compression and animation. We also discuss limitations of current methods and research work needed in the future.

scholarly journals Instagram Image Filtration with Computer Vision

2021 ◽  
Author(s):  
Tanjimul Ahad Asif ◽  
Baidya Nath Saha
Keyword(s):  
Image Processing ◽  
Human Face ◽  
Image Processing Techniques ◽  
Search Results ◽  
Search Result ◽  
Face Images ◽  
Image Filtration ◽  
The Face ◽  
Processing Techniques ◽  
Human Faces

Instagram is one of the famous and fast-growing media sharing platforms. Instagram allows users to share photos and videos with followers. There are plenty of ways to search for images on Instagram, but one of the most familiar ways is ’hashtag.’ Hashtag search enables the users to find the precise search result on Instagram. However, there are no rules for using the hashtag; that is why it often does not match the uploaded image, and for this reason, Users are unable to find the relevant search results. This research aims to filter any human face images on search results based on hashtags on Instagram. Our study extends the author’s [2] work by implementing image processing techniques that detect human faces and separate the identified images on search results based on hashtags using the face detection technique.

scholarly journals Analysis of Buffer Zones of Limestone Mines Areas using Digital Image Processing Techniques

2020 ◽  
Vol 8 (6) ◽  
pp. 5431-5437
Keyword(s):  
Image Processing ◽  
Land Use ◽  
Digital Image Processing ◽  
Digital Image ◽  
Land Use Changes ◽  
Research Work ◽  
Mining Activities ◽  
Buffer Zones ◽  
Image Processing Techniques ◽  
Processing Techniques

The economic growth of any country crucially depends on the mining activity of that country. The mining activities require huge land for the extraction of mineral from the earth. The recent government policy imposing the systematic mapping of the land use and land cover in and around the mines. In the present study, work, the analysis of land used and land covered was carried out at Malkapur limestone mines. This study discussed the brief mapping of the buffer zones buffer zones areas in by using digital image processing techniques. This research work demonstrated the changes happened in and around mines for the buffer radius of 1 km, 5 km and 10 km. In this study it was found that there were no significant changes observed in land use which intern implies that mining activities are not having any impact in land use changes. Further, in this study, not much variation was reported against the forest land and water bodies situated in and around the mines

scholarly journals Quantum-Assisted Retinal Drusen Detection Algorithm using Entropy-Based Image Processing Techniques

2020 ◽  
Vol 9 (3) ◽  
pp. 2251-2256
Keyword(s):  
Image Processing ◽  
Composite System ◽  
Detection Method ◽  
Research Work ◽  
Detection Algorithm ◽  
Image Processing Techniques ◽  
Sensitivity Specificity ◽  
Processing Techniques ◽  
Retinal Fundus ◽  
Retinal Drusen

Drusen identification is the fundamental operation in the automated diagnosis of eye diseases. Manual and automatic detection of the drusen in the retinal fundus images has been developed recently in the classical manner only. This work provides the quantum-based retinal drusen detection method using entropy-based image processing techniques. This algorithm is the composite system of two channels, classical and quantum channels for the preprocessing and drusen detection respectively. This research work has been evaluated with the databases of DRIVE, STARE, MESSIDOR, E-Optha-Ex and ONH-Hunter. This quantum-based approach will be analyzed with the results of the existing classical methods and proves its efficiency from the calculations of sensitivity, specificity, accuracy and execution time.

scholarly journals Detection and Classification of Rice Diseases: An Automated Approach Using Textural Features

2019 ◽  
Vol 38 (1) ◽  
pp. 239-250 ◽  
Author(s):  
Komal Bashir ◽  
Mariam Rehman ◽  
Mehwish Bari
Keyword(s):  
Image Processing ◽  
Research Work ◽  
Recall Rate ◽  
Misclassification Rate ◽  
Maximum Efficiency ◽  
Support Vector ◽  
Image Processing Techniques ◽  
Effective Decision Making ◽  
Processing Techniques

Image processing techniques are widely used for the detection and classification of diseases for various plants. The structure of the plant and appearance of the disease on the plant pose a challenge for image processing. This research implements SVM (Support Vector Machine) based image-processing approach to analyze and classify three of the rice crop diseases. The process consists of two phases, i.e. training phase and disease prediction phase. The approach identifies disease on the leaf using trained classifier. The proposed research work optimizes SVM parameters (gamma, nu) for maximum efficiency. The results show that the proposed approach achieved 94.16% accuracy with 5.83% misclassification rate, 91.6% recall rate and 90.9% precision. These findings were compared with image processing techniques discussed in review of literature. The results of comparison conclude that the proposed methodology yields high accuracy percentage as compared to the other techniques. The results obtained can help the development of an effective software solution by incorporating image processing and collaboration features. This may facilitate the farmers and other bodies in effective decision making to efficiently protect the rice crops from substantial damage. While considering the findings of this research, the presented technique may be considered as a potential solution for adding image processing techniques to KM (Knowledge Management) systems.

scholarly journals Applications of Human Biometrics in Digital Image Processing

2020 ◽  
Vol 5 (7) ◽  
pp. 1273-1276
Author(s):  
Anshul Kumar Singh ◽  
Brajesh Kumar Singh
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Research Work ◽  
Security Systems ◽  
Image Processing Techniques ◽  
Work Related ◽  
Microscope Imaging ◽  
Processing Techniques ◽  
Biometric Features

Digital image processing is the trending topic of research in recent time and big amount of research work related to Biometric features is done and currently it achieved good amount of accuracy. Biometric features is used for security, verification and recognition purpose. This paper is a showcase of how security systems can be developed by using biometric features of human like face, fingerprint and iris, etc. It can be used for the purpose of identification, recognition and Authentication and it is also applicable for making software for image preparation in bioscience laboratories that make use of scanned or digitally photographed images. The widespread use of such image processing techniques using photography and microscope imaging across the natural science with particular attention being paid to research in cell and molecular bioscience. This paper is a review of various methods trending to the field of biometric applications on biotechnologies.

Extraction the Facial Features of the Human Face

2018 ◽  
Author(s):  
Farah Al-khalidi
Keyword(s):  
Image Processing ◽  
Skin Color ◽  
Facial Features ◽  
Horizontal Line ◽  
Human Face ◽  
Image Processing Techniques ◽  
Face Area ◽  
Important Region ◽  
Elliptical Area ◽  
Processing Techniques

This project presents a new approach for automatically tracking the human face as well as facial features (nose, mouth, eyes)in a clear way. This technique became required in various future visual communication applications, such as teleconferencing, Facial recognition systems, Biometrics and Human computer interface etc. The principle behind detecting the face feature is used to measure the respiration rate in the future as the nose represents the important region in the human face for breathing. Human face detection as elliptical area was investigated then image processing techniques were used to extract human face as elliptical area from the rest of image. Several techniques were applied to detect the nose inside the elliptical area as rectangle region and then the mouth and eyes regions were extracted inside the elliptical face area. A skin-color segmentation with image processing techniques played an important role in detecting the human face as elliptic area and then several techniques were used such as enhancement, thresholding, Morphological, edge detections as well as binarization techniques to achieve the aims of the suggested methods. Nose detection as a rectangle region was also investigated by looking for the longest vertical line in the elliptical area. The nose was detected and extracted as rectangle region. Detecting the mouth was achieved by looking for the longest horizontal line under the tip of the nose then thresholding this region to detect the lips of the mouth; by extracting the points of the lips corners we extracted the mouth as elliptical region. Finally, the eye regions were tracked in the upper part of ellipse above the tip of the nose and detected as rectangular regions. Further work is in progress to enhance these techniques to take place in real time images as well as apply them in the medical field.

scholarly journals Categorization of Vehicle and Motion Analysis Using Vehicle Features

2018 ◽  
Vol 7 (3.10) ◽  
pp. 184
Author(s):  
Ms S.Vanithamai ◽  
Dr S.Purushothaman
Keyword(s):  
Image Processing ◽  
Object Detection ◽  
Motion Analysis ◽  
Digital Image Processing ◽  
Digital Image ◽  
Research Work ◽  
Vehicle Classification ◽  
Image Processing Techniques ◽  
Video Frames ◽  
Processing Techniques

This research work can identify the vehicle and classify the vehicle using the vehicle features such as shape, color etc., The parameters extracted from the vehicle classification are based on movement of the vehicle are classified as static, movement variation in the successive video frames are used to identify the hazardness of the vehicle. Digital Image processing techniques are used in the object detection. 

scholarly journals Image To Speech Synthesizer with Reference to Assamese Numerals

2019 ◽  
Vol 9 (1) ◽  
pp. 900-905
Keyword(s):  
Image Processing ◽  
Template Matching ◽  
Research Work ◽  
Second Phase ◽  
Digital Form ◽  
Speech Synthesizer ◽  
Image Processing Techniques ◽  
Digital World ◽  
Matching Technique ◽  
Processing Techniques

In this research work we have shown the methodology for converting printed Assamese numerals to its corresponding utterance. We have implemented as an initial effort which will read only four digit numerals. We are using Image processing techniques to convert an image of Assamese numerals into textual/digital form. In the second phase the numerals will be pronounced as a number by Google speaker. In this system, images are stored in a dataset and then inputted data is compared with the dataset image using template matching technique. After recognition of the text output will be displayed as a speech waveform. This work has many applications in today’s digital world

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