scholarly journals Python - Based Image Processing

2021 ◽  
Vol 9 (11) ◽  
pp. 635-638
Author(s):  
Mrs. Asha K H ◽  
Manjunathswamy B E ◽  
Mrs. Chaithra A S
Keyword(s):  
Image Processing ◽  
Image Process ◽  
Picture Processing ◽  
Graphical Information ◽  
Printing Processes

The main goal of the Image Process project is to extract important information from photographs. The machine may produce a description, interpretation, and comprehension of the scene based on this extracted data. The main goal of image processing is to transform photos in the desired way. This technique allows users to obtain the text of picture processing printing processes and to save the data to disc in a variety of formats. In other terms, image processing is the process of neutering and analysing graphical information in photographs. In our lives, we frequently come across many types of image processing. The clearest example of image processing in our lives is our brain's perceiving of visuals. Once we perceive pictures with our eyes, the process takes relatively little time

scholarly journals Discussion on Redesign of Image from Digital Printing Process

2017 ◽  
Vol 2 (2) ◽  
pp. 45
Author(s):  
Mingying Luo
Keyword(s):  
Image Processing ◽  
Digital Image ◽  
Digital Technology ◽  
Processing Method ◽  
Separation Method ◽  
Digital Printing ◽  
Image Process ◽  
Digital Image Process ◽  
Printing Technology ◽  
Printing Quality

Digital printing is an indispensable link in the modern printing technology. It is the traditional pre-press process on the transition to digital technology in imaging technology, the digital printing technology. Digital printing expounds digital image process in the design means and methods and their influences on the printing quality from the angle of separation method, image processing method, etc..

The Impact Point Detecting System for Photo-Electricity Targets

2013 ◽  
Vol 756-759 ◽  
pp. 399-402
Author(s):  
Zhi Hui Xu ◽  
Wei Zhong Li ◽  
Yong Jun Xiao
Keyword(s):  
Image Processing ◽  
System Design ◽  
Simulation Experiment ◽  
Detection Method ◽  
Image Process ◽  
Impact Point ◽  
Ring Number ◽  
Orientation Method ◽  
The Impact

according to the requirement of shooting training, the impact point detecting system of photo-electricity target is designed based on laser coordinate orientation method. The principle of detection method based on image process is firstly discussed, then the system design and image processing arithmetic is also detailed, at last the simulation experiment is done, and the result shows that the designed system is stabilized and can reach accurate and reliable detecting and displaying for scoring ring number.

Study on Otsu Threshold Method for Image Segmentation Based on Genetic Algorithm

2014 ◽  
Vol 998-999 ◽  
pp. 925-928 ◽  
Author(s):  
Zhi Bo Xu ◽  
Pei Jiang Chen ◽  
Shi Li Yan ◽  
Tai Hua Wang
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Image Segmentation ◽  
Image Process ◽  
Segmentation Method ◽  
Threshold Method ◽  
Threshold Segmentation ◽  
Maximum Variance ◽  
Segmentation Image ◽  
Selection Of

Threshold segmentation method was widely applied in image process and the selection of threshold affected the final results of image segmentation to a large extent. In order to improve the accuracy and the calculation speed of image segmentation, an Otsu threshold segmentation method based on genetic algorithm was offered. According to the threshold and the gray scale values of pixels, the pixels were divided into two categories, and then the genetic algorithm was used to find the maximum variance between clusters and obtain the optimal threshold of segmentation image. The experimental results show that this method can be used to segment the image effectively, which make the basis for image processing and analysis in the next step.

Optimizing of Light Stripe Image Acquisition in Light Section Method Measurement

2013 ◽  
Vol 475-476 ◽  
pp. 366-369
Author(s):  
Rui Yin Tang ◽  
Peng Fei Li
Keyword(s):  
Image Processing ◽  
Image Acquisition ◽  
Experimental Results ◽  
Special Method ◽  
Image Process ◽  
High Quality ◽  
Section Method ◽  
Light Section ◽  
Parameters Selection ◽  
Quality Profile

This paper proposed a method to acquire high quality profile image based on a serious of special parameters selection and setting.And to deal with the un-matching between the speed of image grabbing and image processing,we use a special method to grab and process image in parallel based on Halcon platform. The experimental results obtained the high quality light stripe image that could increase the efficiency of measurement and simplify the image process algorithm.

A Research for Image Defogging Algorithm

2013 ◽  
Vol 409-410 ◽  
pp. 1653-1656 ◽  
Author(s):  
Yu Fan ◽  
Xue Feng Wu
Keyword(s):  
Image Processing ◽  
Image Restoration ◽  
Physical Model ◽  
Digital Image Processing ◽  
Digital Image ◽  
Computational Photography ◽  
Processing Technology ◽  
Image Process ◽  
Image Defogging ◽  
Resolution Algorithm

Computational photography and image processing technology are used to restore the clearness of images taken in fog scenes autmatically.The technology is used to restore the clearness of the fog scene,which includes digital image processing and the physical model of atmospheric scattering.An algorithm is designed to restore the clearness of the fog scene under the assumption of the albedo images and then the resolution algorithm is analysised.The algorithm is implemented by the software of image process ,which can improve the efficiency of the algorithm and interface.The fog image and defogging image are compared, and the results show that the visibility of the image is improved, and the image restoration is more clearly .

Design of a High-Reliability FPGA Platform for High-Resolution Image Process System

2015 ◽  
Vol 764-765 ◽  
pp. 1283-1287
Author(s):  
Wen Tzeng Huang ◽  
Hung Li Tseng ◽  
Jian Cheng Dai ◽  
Chin Hsing Chen ◽  
Sun Yen Tan
Keyword(s):  
Image Processing ◽  
High Speed ◽  
High Reliability ◽  
Processing System ◽  
Simulation Software ◽  
Image Process ◽  
Image Processing System ◽  
Signal Line ◽  
Process System ◽  
Standard Value

With continuous advancement in science and technology, the image quality has entered an era of full-HD. This study developed a high-reliability image processing system platform, based on the FPGA platform. By using a high-reliability hardware platform development process, and with the aid of the simulation software, this study simulated the transmission integrity of the high-speed digital signals on the PCB. The proposed method was used to build a FPGA-based high-reliability image processing system platform. The implementation in this study, with the length of the Clock and DQS signal line of DDR2 being controlled within 555 mil, was discussed, and the errors were analyzed. The simulated value of the tDQSCK was 195.048 ps, the measured value was 215 ps, and the standard value of the JEDEC was less than 350 ps. Between the simulated value and the measured value, there was only an error of about 9.3%, which meets the reliability requirement. The length tolerance of the signal line laid was 38.5% better than the standard value of the JEDEC.

Hydraulic Focusing Stability Detection Method Study Based on Digital Image Processing Technology

2012 ◽  
Vol 591-593 ◽  
pp. 1839-1843
Author(s):  
Lu Xiao ◽  
Lu Zhang ◽  
Hong Zhao ◽  
Wei Chen ◽  
Li Yuan
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Experimental Error ◽  
Detection Method ◽  
Processing Technology ◽  
Image Process ◽  
Process Technology ◽  
Good Reliability ◽  
Image Processing Technology

Hydraulic focusing technology is an important method in many researches about particles. But there is no reported direct real-time detection method to survey its stability. A novel and high resolution method is put forward, which is based on digital image processing technology to detect hydraulic focusing stability. And five parameters are designed to assess its stable performance. A set of experiments is implemented with different sample and buffer hydraulic focusing forming velocities, and the results and experimental error are discussed seriously. The conclusion can be drawn by the final experimental error analysis which is less than during all the detection course. It can be proved that this hydraulic focusing stability detection method based on digital image process technology has the advantages of the excellent precision, the fast processing speed and the good reliability.

scholarly journals Brain Tumor Detection by using Fcm Algorithm

2020 ◽  
Vol 9 (4) ◽  
pp. 1856-1862
Keyword(s):  
Image Processing ◽  
Input Image ◽  
Contour Detection ◽  
Optimization Techniques ◽  
Video Frame ◽  
Image Process ◽  
Core Analysis ◽  
Accuracy Level ◽  
Process System ◽  
Processing Techniques

capable of changing a picture into digital type and it perform operations on image. In image process, input is a picture (may be a video frame or a photograph in any format) and therefore the output is also a picture or the characteristics of the input image. Image process system sometimes considers a picture as a 2 dimensional signal, whereas process. It’s one in all the rising technologies, with its branches of application widespread into many domains of business. Image process may be a core analysis in space engineering and it additionally acts as a thrust space in alternative disciplines of applied science. Researchers would like to do perform research in image processing; because it offers real time applications and therefore the results derived from image processing techniques are created. In this paper we have discussed about the greedy snake segmentation, snake contour detection and fcm optimization techniques for segmenting the tumor image, the accuracy level is increased up to 90% compared with the existing algorithm.

scholarly journals An Enhanced K-Means Clustering Based on K- SVD_DWT Algorithm for Image Segmentation

2019 ◽  
Vol 8 (11S) ◽  
pp. 634-640
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Morphological Characteristics ◽  
User Interaction ◽  
Estimation Procedure ◽  
Vital Role ◽  
Discrete Wavelet ◽  
Image Process ◽  
Processing Task ◽  
Value Decomposition

The complete nature of the image geared by various processes but image segmentation plays vital role. For object illustration, image analysis, visualization and image processing task the image is segmented into useful information by image segmentation. The image is segmented with respect to the opted scenario by image segmentation. The image measurements like texture, color and depth are considered by the segmentation. The plant disease can be spotted and classified in the field of agriculture and image segmentation is essential in image processing. Based on the morphological characteristics of plants, the diseases can be classified. Image segmentation is of importance within the field of image process. This work focuses on K-means Singular Value Decomposition (K-SVD) and Discrete Wavelet Transform (DWT) that is associated with Kmeans clustering for effectual image segmentation of leaf. Image segmentation is the basic pre-processing task to segregate the leaves in several image process applications. The most challenge in analyzing the plant images are locating and segmenting plants. Image segmentation accustomed to discover the objects and limits such as lines, curves, etc. in images. K-means cluster algorithmic program is wide employed in image segmentation to its machine simplicity. However, the clump results obtained from K-means heavily rely on the initial parameters. Mostly, these initial parameters are elite through hit and trial rule that ends up in inconsistency within the image segmentation results. In this work, an improved K-means cluster algorithmic program is projected for image segmentation, using a histogram based mostly initial parameter estimation procedure. To boot, the projected algorithmic program needs less user interaction to work out K-means data format parameters. Some experiments are conducted supported numerous gray images to check the projected approach. The experiment results show that the projected approach will improve the K-means based mostly image segmentation results

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