An image texture is a set of metrics calculated in image processing designed to quantify the perceived texture of an image. Image Texture gives us information about the spatial arrangement of color or intensities in an image or selected region of an image. This presentation consists of its types, uses, methods and approaches.
This paper proposed a facial expression recognition approach based on Gabor wavelet transform. Gabor wavelet filter is first used as pre-processing stage for extraction of the feature vector representation. Dimensionality of the feature vector is reduced using Principal Component Analysis and Local binary pattern (LBP) Algorithms. Experiments were carried out of The Japanese female facial expression (JAFFE) database. In all experiments conducted on JAFFE database, results obtained reveal that GW+LBP has outperformed other approaches in this paper with Average recognition rate of 90% under the same experimental setting.
This paper proposed a facial expression recognition approach based on Gabor wavelet transform. Gabor wavelet filter is first used as pre-processing stage for extraction of the feature vector representation. Dimensionality of the feature vector is reduced using Principal Component Analysis and Local binary pattern (LBP) Algorithms. Experiments were carried out of The Japanese female facial expression (JAFFE) database. In all experiments conducted on JAFFE database, results obtained reveal that GW+LBP has outperformed other approaches in this paper with Average recognition rate of 90% under the same experimental setting.
A multispectral image is one that captures image data from two or more ranges of frequencies along the spectrum, such as visible light and infrared energy.
In multispectral images, the same spatial region is captured multiple times using different imaging modalities.
This presentation is about the raster and vector data in GIS which is important and costly as well, through the presentation we will learn about both type of data.
This Ppt is based on the Raster animation . It explains u ablout a brief idea bout the Raster Graphics its Working with Real time Animation Examples that are used in our day to day life.
The following points are covered in this ppt
1. Introduction
2. Working of Raster Animation
3. Types of Raster Animations Modern and Traditional
4. Examples
5.Applications
6. Advantages
7. Disadvantages
3D Display Methods:
In this section, we focus on a subgoals of realistic picture. This co-ordinate reference defines the position and orientation for the planeof the camera, as shown in next slide.This plane must be used to display a view of the object; its description has to transferred to thecamera reference co-ordinates and projected onto the selected display plane. Then we can displayobject in wire frame form or we can apply lighting and surface rendering techniques to shade thevisible surfaces
Radiometric corrections include correcting the data for sensor irregularities and unwanted sensor or atmospheric noise, and converting the data so they accurately represent the reflected or emitted radiation measured by the sensor.
DOMAIN SPECIFIC CBIR FOR HIGHLY TEXTURED IMAGEScseij
It is A Challenging Task To Build A Cbir System Which Primarily Works On Texture Values As There
Meaning And Semantics Needs A Special Care To Be Mapped With Human Based Languages. We Have
Consider Highly Textured Images Having Properties(Entropy, Homogeneity, Contrast, Cluster Shade, Auto
Correlation)And Have Mapped Using A Fuzzy Minmax Scale W.R.T. Their Degree(High, Low,
Medium)And Technical Interpetation.This Developed System Is Performing Well In Terms Of Precision
And Recall Value Showing That Semantic Gap Has Been Reduced For Highly Textured Images Based Cbir.
A multispectral image is one that captures image data from two or more ranges of frequencies along the spectrum, such as visible light and infrared energy.
In multispectral images, the same spatial region is captured multiple times using different imaging modalities.
This presentation is about the raster and vector data in GIS which is important and costly as well, through the presentation we will learn about both type of data.
This Ppt is based on the Raster animation . It explains u ablout a brief idea bout the Raster Graphics its Working with Real time Animation Examples that are used in our day to day life.
The following points are covered in this ppt
1. Introduction
2. Working of Raster Animation
3. Types of Raster Animations Modern and Traditional
4. Examples
5.Applications
6. Advantages
7. Disadvantages
3D Display Methods:
In this section, we focus on a subgoals of realistic picture. This co-ordinate reference defines the position and orientation for the planeof the camera, as shown in next slide.This plane must be used to display a view of the object; its description has to transferred to thecamera reference co-ordinates and projected onto the selected display plane. Then we can displayobject in wire frame form or we can apply lighting and surface rendering techniques to shade thevisible surfaces
Radiometric corrections include correcting the data for sensor irregularities and unwanted sensor or atmospheric noise, and converting the data so they accurately represent the reflected or emitted radiation measured by the sensor.
DOMAIN SPECIFIC CBIR FOR HIGHLY TEXTURED IMAGEScseij
It is A Challenging Task To Build A Cbir System Which Primarily Works On Texture Values As There
Meaning And Semantics Needs A Special Care To Be Mapped With Human Based Languages. We Have
Consider Highly Textured Images Having Properties(Entropy, Homogeneity, Contrast, Cluster Shade, Auto
Correlation)And Have Mapped Using A Fuzzy Minmax Scale W.R.T. Their Degree(High, Low,
Medium)And Technical Interpetation.This Developed System Is Performing Well In Terms Of Precision
And Recall Value Showing That Semantic Gap Has Been Reduced For Highly Textured Images Based Cbir.
Texture Unit based Approach to Discriminate Manmade Scenes from Natural Scenesidescitation
In this paper a method is proposed to discriminate
natural and manmade scenes of similar depth. Increase in
image depth leads to increase in roughness in manmade
scenes; on the contrary natural scenes exhibit smooth behavior
at higher image depth. This particular arrangement of pixels
in scene structure can be well explained by local texture
information in a pixel and its neighborhood. Our proposed
method analyses local texture information of a scene image
using texture unit matrix. For final classification we have
used unsupervised learning using Self Organizing Map
(SOM). This technique is useful for online classification due
to very less computational complexity.
Texture Unit based Monocular Real-world Scene Classification using SOM and KN...IDES Editor
In this paper a method is proposed to discriminate
real world scenes in to natural and manmade scenes of similar
depth. Global-roughness of a scene image varies as a function
of image-depth. Increase in image depth leads to increase in
roughness in manmade scenes; on the contrary natural scenes
exhibit smooth behavior at higher image depth. This particular
arrangement of pixels in scene structure can be well explained
by local texture information in a pixel and its neighborhood.
Our proposed method analyses local texture information of a
scene image using texture unit matrix. For final classification
we have used both supervised and unsupervised learning using
K-Nearest Neighbor classifier (KNN) and Self Organizing
Map (SOM) respectively. This technique is useful for online
classification due to very less computational complexity.
Texture Segmentation Based on Multifractal Dimensionijsc
Texture segmentation can be considered the most important problem, since human can distinguish different
textures quit easily, but the automatic segmentation is quit complex and it is still an open problem for
research. In this paper focus on implement novel supervised algorithm for multitexture segmentation and
this algorithm based on blocking procedure where each image divide into block (16×16 pixels) and extract
vector feature for each block to classification these block based on these feature. These feature extract
using Box Counting Method (BCM). BCM generate single feature for each block and this feature not
enough to characterize each block ,therefore, must be implement algorithm provide more than one slide for
the image based on new method produce multithresolding, after this use BCM to generate single feature for
each slide.
Texture Segmentation Based on Multifractal Dimension ijsc
Texture segmentation can be considered the most important problem, since human can distinguish different textures quit easily, but the automatic segmentation is quit complex and it is still an open problem for research. In this paper focus on implement novel supervised algorithm for multitexture segmentation and this algorithm based on blocking procedure where each image divide into block (16×16 pixels) and extract vector feature for each block to classification these block based on these feature. These feature extract using Box Counting Method (BCM). BCM generate single feature for each block and this feature not enough to characterize each block ,therefore, must be implement algorithm provide more than one slide for the image based on new method produce multithresolding, after this use BCM to generate single feature for each slide.
SEGMENTATION USING ‘NEW’ TEXTURE FEATUREacijjournal
Color, texture, shape and luminance are the prominent features for image segmentation. Texture is an
organized group of spatial repetitive arrangements in an image and it is a vital attribute in many image
processing and computer vision applications. The objective of this work is to segment the texture sub
images from the given arbitrary image. The main contribution of this work is to introduce “NEW” texture
feature descriptor to the image segmentation field. The NEW texture descriptor labels the neighborhood
pixels of a pixel in an image as N,W,NW,NE,WW,NN and NNE(N-North, W-West).To find the prediction
value, the gradient of the intensity functions are calculated. Eight component binary vectors are formed
and compared to prediction value. Finally end up with 256 possible vectors. Fuzzy c-means clustering is
used to segment the similar regions in textural image Extensive experimentation shows that the proposed
methodology works better for segmenting the texture images, and also segmentation performance are
evaluated.
OTSU Thresholding Method for Flower Image Segmentationijceronline
Segmentation is basic process in image processing. It always produces an effective result for next process. In this paper, we proposed the flower image segmentation. Oxford flower collection is used for segmentation.Different segmentation techniques are available. Different techniques and algorithm are developed to describe the segmentation.We proposed a OTSU thresholding technique for flower image segmentation in this paper. which gives good result as compared with the other methods and simple also.Segmentation subdivide the image into different parts.firstly, segmentation techniques and then otsu thresholding method described in this paper.CIE L*a*b color space is used in thresholding for better results.Thresholding apply seperatly on each L, a and b component. accordingly the features can be extracted like shape, color, texture etc. finally, results with the flower images are shown.
Content Based Image Retrieval (CBIR) is one of the
most active in the current research field of multimedia retrieval.
It retrieves the images from the large databases based on images
feature like color, texture and shape. In this paper, Image
retrieval based on multi feature fusion is achieved by color and
texture features as well as the similarity measures are
investigated. The work of color feature extraction is obtained by
using Quadratic Distance and texture features by using Pyramid
Structure Wavelet Transforms and Gray level co-occurrence
matrix. We are comparing all these methods for best image
retrieval
ER Publication,
IJETR, IJMCTR,
Journals,
International Journals,
High Impact Journals,
Monthly Journal,
Good quality Journals,
Research,
Research Papers,
Research Article,
Free Journals, Open access Journals,
erpublication.org,
Engineering Journal,
Science Journals,
A combined method of fractal and glcm features for mri and ct scan images cla...sipij
Fractal analysis has been shown to be useful in image processing for characterizing shape and gray-scale
complexity. The fractal feature is a compact descriptor used to give a numerical measure of the degree of
irregularity of the medical images. This descriptor property does not give ownership of the local image
structure. In this paper, we present a combination of this parameter based on Box Counting with GLCM
Features. This powerful combination has proved good results especially in classification of medical texture
from MRI and CT Scan images of trabecular bone. This method has the potential to improve clinical
diagnostics tests for osteoporosis pathologies.
Colour-Texture Image Segmentation using Hypercomplex Gabor Analysissipij
Texture analysis such as segmentation and classification plays a vital role in computer vision and pattern recognition and is widely applied to many areas such as industrial automation, bio-medical image processing and remote sensing. In this paper, we first extend the well-known Gabor filters to color images using a specific form of hypercomplex numbers known as quaternions. These filters are
constructed as windowed basis functions of the quaternion Fourier transform also known as hypercomplex Fourier transform. Based on this extension this paper presents the use of these new
quaternionic Gabor filters in colour texture image segmentation. Experimental results on two colour texture images are presented. We tested the robustness of this technique for segmentation by adding Gaussian noise to the texture images. Experimental results indicate that the proposed method gives better segmentation results even in the presence of strongest noise.
A comparative study on content based image retrieval methodsIJLT EMAS
Content-based image retrieval (CBIR) is a method of
finding images from a huge image database according to persons’
interests. Content-based here means that the search involves
analysis the actual content present in the image. As database of
images is growing daybyday, researchers/scholars are searching
for better techniques for retrieval of images maintaining good
efficiency. This paper presents the visual features and various
ways for image retrieval from the huge image database.
Noise tolerant color image segmentation using support vector machineeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
3. Definition
An image texture is a set of metrics calculated in
image processing designed to quantify the perceived
texture of an image.
Regular repetition of an element or pattern on a
surface.
Image Texture gives us information about the
spatial arrangement of color or intensities in an image
or selected region of an image.
Texture can be defined as an entity consisting of
mutually related pixels and group of pixels.
4. Definition(contd…)
In fact, there are many ways in which intensity
might vary, but if the variation does not have
sufficient uniformity, the texture may not be
characterized, sufficiently close to permit recognition
or segmentation.
Thus, the degrees of randomness and of regularity
will have to be measured and compared when
charactering a texture.
Often, textures are derived from tiny objects or
components that are themselves similar, but that are
placed together in ways ranging from purely random
to purely regular, such as bricks in a wall, or grains of
sand, etc.
5. Texture Analysis
Image textures can be artificially created or found
in natural scenes captured in an image.
Since the repetitive local arrangement of intensity
determines the texture, we have to analyze
neighborhoods of pixels to measure texture
properties.
Because texture has so many different dimensions
no single method of texture representation that is
adequate for a variety of textures.
7. Algorithm
Step1 : Read Image from database x=image.
Step2 : If image in color then convert into grayscales.
Step3 : Apply any one filter on image.
Step4 : If extract region then
Step5 : Display the Segmented Image.
else
Step6 : Repeat step 3.
Step7 : Stored in database.
9. Tactile Texture
We perceive it by touching an object
Every material has a different touch, so it is a
different texture
10. Visual Texture
When we represent a tactile texture using graphic
elements, we get a visual texture.
We can create visual textures using different art
procedures: scrapping, stencilling, printing
11. Natural Texture
They belong to natural elements, like the skin of an
elephant, the cortex of a tree or the surface of a rose
Patel.
12. Artificial Texture
The surface of any object made by us: steel, paper,
different kinds of fabrics.
Artificial textures are created and designed by
human beings for a specific purpose to give a sense
of volume.
13. Why do we use texture?
To identify different textured and nontextured
regions in an image.
To classify/segment different texture regions in an
image.
To extract boundaries between major texture
regions.
Analyze texture in CGAnalyze texture in CG
Structured approach Statistical approach
14. Texture Segmentation
Image texture can be used as a description for
regions into segments
Can be supervised or unsupervised depending on if
prior knowledge about the image or texture class is
available.
Supervised-identifies and separates one or more
regions that match texture properties shown in the
training textures.
Unsupervised-first recover different texture classes
from an image before separating them into regions.
15. Methods Used for Texture Segmentation
Gabor filter
Edge detection
Thresholding
Histogram based
Region based
16. Gabor Filter
It is a linear filter used for edge detection.
Frequency and orientation representations are
similar to those of the human visual system.
Appropriate for texture representation and
discrimination.
A two dimensional Gabor function g(x, y) is
defined as:
17. Histogram Matching
Compute the histogram of the template.
Sweep a window over the image.
Compute the histogram of the window.
Do a correlation between the histograms.
the texture we
are searching
(template)
window at step k
(thr sample)
window at k+1
19. Texel
Can be called as texture element, texel pixel
Fundamental unit of texture space used in computer
graphics
Textures are represented by array of texels, just as
pictures are represented by arrays of pixels
20. Statistical approach
Texture Is a spatial
property.
A simple one-
dimensional Histogram
is not useful in
characterizing texture.
Example
( an image in which pixels
Alternate From black to
white in a checkerboard
fashion will have the same
histogram as an image in
which the top half is black
and the bottom half is
white).
21. Types of Statistical Approach
Co occurrence matrix
The gray level co-occurrence matrix approach is
based on studies of the statistics of pixel intensity
distributions.
The co-occurrence matrices express the relative
frequencies (or probabilities) P(i, j | d,θ) with which
two pixels having relative polar coordinates (d,θ)
appear with intensities i, j.
The co-occurrence matrices provide raw numerical
data on the texture, although this data must be
condensed to relatively few numbers before it can be
used to classify the texture.
22. Co occurrence Matrix
To compute such a matrix, we first separate the
intensity in the image into a small number of
different levels.
For example, by dividing the usual brightness
values ranging from 0 to 255 by 64, we create the
levels 0, 1, 2, and 3.
24. Edge Detection
The use of edge detection to determine the number
of edge pixels in a specified region helps determine
a characteristic of texture complexity.
Consider a region with N pixels. the gradient-based
edge detector is applied to this region by producing
two outputs for each pixel p: the gradient magnitude
Mag(p) and the gradient direction Dir(p) then –
The edgeness per unit area can be defined by
F_{edgeness}={|{p | Mag(p) > T}|}/{N} for some
threshold T.
25. Edge Detection
To include orientation with edgeness we can use
histograms for both gradient magnitude and gradient
direction. Let Hmag(R) denote the normalized
histogram of gradient magnitudes of region R, and
let Hdir denote the normalized histogram of gradient
orientations of region R. Both are normalized
according to the size NRThen is quantitative texture
description of region R.
26. Laws Texture Energy Measures
Another approach to generate texture features is to
use local masks to detect various types of textures.
Convolution masks of 5x5 are used to compute the
energy of texture .
Law’s measures use a set of convolution filters to
assess gray level, edges, spots, ripples, and waves
in textures.
This method starts with three basic filters:
averaging: L3 = (1, 2, 1)
first derivative (edges): E3 = (-1, 0, 1)
second derivative (curvature): S3 = (-1, 2, -1)
27. Laws Texture Energy Measures
Convolving these filters with themselves and each
other results in five new filters.
The masks are generated from the following
vectors.
L5 = [ +1 +4 6 +4 +1 ] (Level)
E5 = [ -1 -2 0 +2 +1 ] (Edge)
S5 = [ -1 0 2 0 -1 ] (Spot)
W5 = [ -1 +2 0 -2 +1 ] (Wave)
R5 = [ +1 -4 6 -4 +1 ] (Ripple)
28. Laws Texture Energy Measures
Now we can multiply any two of these vectors, using the
first one as a column vector and the second one as a row
vector, resulting in 5 × 5 Law’s masks.
For example
L5*S5=
Now you can apply the resulting 25 convolution filters to a
given image.
The 25 resulting values at each position in the image are
useful descriptors of the local texture.
29. Use of Texture in education
A texture analyzer can be used to accurately, and
repeatable, test the product to measure numerical
output against the subjective findings.
Food Technology Corporation's texture
measurement systems are in use in schools,
colleges and universities worldwide.
Other uses are in cosmetics, web designing and
auto parts designing etc.
30. Conclusion and References
Imagine the world without texture?
https://www.cs.auckland.ac.nz/~georgy/research/text
https://en.wikipedia.org/wiki/Image_texture
http://ieeexplore.ieee.org/xpl/articleDetails.jsp