CALIBRATION OF OPTICAL SILICONE TACTILE SENSOR

2015 ◽  
Vol 76 (8) ◽  
Author(s):  
Muhammad Azmi Ayub ◽  
Nurul Fathiah Mohamed Rosli ◽  
Abdul Halim Esa ◽  
Amir Abdul Latif ◽  
Roseleena Jaafar
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Tissue Characterization ◽  
Tactile Sensor ◽  
Computer Algorithm ◽  
Image Processing Technique ◽  
Image Processing Algorithm ◽  
Study Results ◽  
Analysis Computer ◽  
Sense Of Touch

This paper presents the calibration and development of a computer algorithm to analyze the deformation behavior of the changes in the diameter of a silicone tactile sensor using an image processing technique. In addition, the scope of the work also aims to evaluate the sensor’s sensitivity. Unfortunately, the current design and the system of tactile sensor is not suitable for soft tissue characterization because the sensor system uses multiple optical waveguide transduction technique which is relatively large in diameter size, not flexible and less accurate which is lack of ‘sense of touch’. Hence, an image processing algorithm has been developed using image processing software. The results indicate significant increase in the change in the diameter images. The overall image analysis technique involves the following main stages: image acquisition (capturing of images) and image processing (thresholding, noise filtering, component labeling, and geometric properties). The use of fiber scope and as well as an effective image analysis computer algorithm will facilitate and automate the process for sensing information. This study results in finding the mathematical model of a new technique to establish the sensitivity value of the silicon tactile sensor where a higher sensitivity indicates a more sensitive sensor. The outcomes of this research shows that the functionality of the developed new image analysis computer algorithm technique is suitable to establish the sensing information on the ‘sense of touch’ such as hardness, roughness and other physical characteristics of the surfaces.

scholarly journals Flight Performance Analysis of an Image Processing Algorithm for Integrated Sense-and-Avoid Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Lidia Forlenza ◽  
Giancarmine Fasano ◽  
Domenico Accardo ◽  
Antonio Moccia
Keyword(s):  
Image Processing ◽  
Performance Analysis ◽  
Data Rate ◽  
Obstacle Detection ◽  
Image Processing Technique ◽  
Identification System ◽  
Flight Performance ◽  
Image Processing Algorithm ◽  
Position Measurement ◽  
Detection Range

This paper is focused on the development and the flight performance analysis of an image-processing technique aimed at detecting flying obstacles in airborne panchromatic images. It was developed within the framework of a research project which aims at realizing a prototypical obstacle detection and identification System, characterized by a hierarchical multisensor configuration. This configuration comprises a radar, that is, the main sensor, and four electro-optical cameras. Cameras are used as auxiliary sensors to the radar, in order to increase intruder aircraft position measurement, in terms of accuracy and data rate. The paper thoroughly describes the selection and customization of the developed image-processing techniques in order to guarantee the best results in terms of detection range, missed detection rate, and false-alarm rate. Performance is evaluated on the basis of a large amount of images gathered during flight tests with an intruder aircraft. The improvement in terms of accuracy and data rate, compared with radar-only tracking, is quantitatively demonstrated.

scholarly journals Brain Tumor Segmentation using Multi Level Thresholding using Fuzzy Entropy

2020 ◽  
Vol 8 (5) ◽  
pp. 2641-2643
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Image Segmentation ◽  
Brain Tumor ◽  
Fuzzy Entropy ◽  
Image Processing Technique ◽  
Tumor Segmentation ◽  
Fuzzy Approach ◽  
Segmentation Process ◽  
Multi Level

In image processing field, image processing technique is used to distinguish the object from its image scene at pixel level. The image segmentation process is the significant task in the processing of image field as well as in image analysis. The most difficult task in the image analysis field is the automatic separation of object from its background. To alleviate this problem several image segmentation process is introduced are gray level thresholding, edge detection method, interactive pixel classification method, neural network approach and segmentation based on fuzzy approach This chapter presents the multilevel set thresholding method using partition of fuzzy approach on brain image histogram and theory of entropy. The fuzzy entropy method is applied on multi-level brain tumor MRI image segmentation method. The threshold of brain MR image is obtained by optimized the entropy measure. In this method, Differential Evolution technique is used to find the best solution.

scholarly journals A novel automatic image processing algorithm for detection of hard exudates based on retinal image analysis

2008 ◽  
Vol 30 (3) ◽  
pp. 350-357 ◽  
Author(s):  
Clara I. Sánchez ◽  
Roberto Hornero ◽  
María I. López ◽  
Mateo Aboy ◽  
Jesús Poza ◽  
...  
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Retinal Image ◽  
Processing Algorithm ◽  
Image Processing Algorithm ◽  
Hard Exudates ◽  
Retinal Image Analysis ◽  
Automatic Image Processing

scholarly journals AN ARTIFICIAL NEURAL PROCESS TO CREATE CONTINUOUS OBJECT BOUNDARIES IN MEDICAL IMAGE ANALYSIS

2014 ◽  
pp. 27-31
Author(s):  
Mahinda Pathegama ◽  
Ozdemir Gol
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Medical Image Analysis ◽  
Directional Sensitivity ◽  
Sensitive Information ◽  
Image Processing Algorithm ◽  
Neural Process ◽  
Sensitivity Derivatives ◽  
Edge Linking ◽  
Artificial Neural

Computer-aided analysis for cell images acquired by an electron microscope involves a range of image processing steps including edge detection and thresholding. The major problem encountered in automatic cell analysis is the possible presence of incomplete boundaries of cell features, which prevent the generation of cell feature details including all measurements as the boundaries include very tiny gaps. This paper presents a novel edge-linking technique based on an artificial neural process, which uses directional sensitivity derivatives from an edged image. The input signals applied to the neural layer are integrated with direction-sensitive information produced by an auxiliary algorithm, which interrogates all the pixels in the 2-D image in order to designate the specified direction in which each edge-end pixel should propagate. The proposed edge-linking technique, implemented as an image-processing algorithm for direction-sensitive selectiveness, provides an effective solution to the problem of porous boundaries encountered in biological cell image analysis.

Application Of Digital Image Processing Technique In Monitoring LNAPL Migration In Double Porosity Soil Column

2015 ◽  
Vol 72 (3) ◽  
Author(s):  
Sa’ari R ◽  
Rahman N. A. ◽  
Abdul Latif H. N. ◽  
Yusof Z. M. ◽  
Ngien S. K. ◽  
...  
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Digital Image ◽  
Soil Column ◽  
Processing Technique ◽  
Double Porosity ◽  
Image Processing Technique ◽  
Future Research ◽  
Saturation Intensity ◽  
Contour Plots

This paper investigates the phenomenon of light non-aqueous phase liquid (LNAPL) migration in double porosity soil. Investigation on the migration of LNAPL in double porosity soil was performed on aggregated kaolin using the digital image analysis. The photographic technique was used to capture the migration of LNAPL in aggregated soil samples. The captured digital images were fed through an image processing code to convert them to the hue-saturation-intensity (HSI) format which were subsequently used to plot the 2D LNAPL migration behaviour. The results of Experiment 1 and 2 show that the LNAPL moved downward faster when the moisture content increased. Another observation was that the kaolin granules started to disintegrate at a water  content of 35%. In conclusion, using image analysis technique has enabled the researchers to monitor and visualize the LNAPL migration in the double porosity soil columns based on HSI values. The contour plots of HSI intensity value has provide detailed and useful information for future research.

scholarly journals The use of color distribution analysis for ripeness prediction of Golden Apollo melon

2017 ◽  
Author(s):  
The Journal of Applied Horticulture ◽  
Usman Ahmad
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Skin Color ◽  
Color Image ◽  
Age Groups ◽  
Processing Algorithm ◽  
Distribution Analysis ◽  
Human Visual Perception ◽  
Image Processing Algorithm ◽  
Color Distribution

Human visual perception on color of melon fruit for ripeness judgement is a complex phenomenon that depends on many factors, making the judgement is often inaccurate and inconsistent. The objective of this study is to develop an image processing algorithm that can be used for distinguishing ripe melons from unripe ones based on their skin color. The image processing algorithm could then be used as a pre-harvest tool to facilitate farmers with enough information for making decisions about whether or not the melon is ready to harvest. Four sample groups of Golden Apollo melon were harvested at four different harvesting age, with 55 fruits in each group. The color distribution as results of the image analysis can be separated at the first two groups from other groups with minimal overlap, but they cannot be separated from the other two groups. The color image analysis of the melons in combination with discriminant analysis could be used to distinguish between harvesting age groups with an average accuracy of 86%.

scholarly journals Locating the 'missing wedge' artifacts from limited-angle CT reconstruction

2018 ◽  
Vol 24 (S2) ◽  
pp. 140-141
Author(s):  
Jianhong Liu ◽  
Yong Guan ◽  
Liang Chen ◽  
Haobo Bai ◽  
Wenbin Wei ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Image Analysis ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Ct Image ◽  
Ct Reconstruction ◽  
Reconstruction Algorithms ◽  
X Ray ◽  
Reconstruction Quality

Abstract:'Missing wedge' problem exists in some kind of CT imaging situations, such as electron microscopy, x-ray nano-CT image, etc. Method such as iterative reconstruction algorithms, total variation based method were applied to improve the reconstruction quality, but the 'missing wedge' artifacts are still inevitable. In this paper, a method based on image processing technique was proposed to locate the 'missing wedge' artifacts in CT reconstruction. The result showed good performance on locating the artifacts, which also showed the potential in CT reconstruction and image analysis in nano-CT.

scholarly journals Developments in Segmentation of Abdominal Liver CT Images for Cancer and Other Disease Lesion Detection

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Hariharan S
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Medical Image Analysis ◽  
Clinical Information ◽  
Disease Diagnosis ◽  
Processing Technique ◽  
Ct Images ◽  
Lesion Detection ◽  
Image Processing Technique ◽  
High Level

Segmentation is one of the most important and widely used methods in medical image analysis. It is considered to be a high level image processing technique and can be used for many applications in medical imaging. CT images are commonly used in medical field and it provides clear picture of the internal organs. However in some places further processing of CT images are required for disease diagnosis and lesion detection. This work is an effort for bringing out clinical information from liver images of computed tomography based on image processing. Finally liver tumor classifications have been performed using texture based image analysis.

A New Image Processing Technique for STEM

1974 ◽  
Vol 32 ◽  
pp. 432-433
Author(s):  
Yasushi Kokubo ◽  
Hirotami Koike ◽  
Teruo Someya
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Scanning Electron Microscopy ◽  
Elastic Scattering ◽  
Field Emission ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Energy Analyzer ◽  
Scanning Microscope ◽  
Scanning Electron

One of the advantages of scanning electron microscopy is the capability for processing the image contrast, i.e., the image processing technique. Crewe et al were the first to apply this technique to a field emission scanning microscope and show images of individual atoms. They obtained a contrast which depended exclusively on the atomic numbers of specimen elements (Zcontrast), by displaying the images treated with the intensity ratio of elastically scattered to inelastically scattered electrons. The elastic scattering electrons were extracted by a solid detector and inelastic scattering electrons by an energy analyzer. We noted, however, that there is a possibility of the same contrast being obtained only by using an annular-type solid detector consisting of multiple concentric detector elements.

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

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