Achievement of Dynamic-Link Library for Image Segmentation Based on LabVIEW

2011 ◽  
Vol 697-698 ◽  
pp. 805-808
Author(s):  
Shi Wei Liu ◽  
Jun Lan Li ◽  
Xing Yu Zhao ◽  
Da Wei Zhang
Keyword(s):  
Image Segmentation ◽  
Dynamic Link Library ◽  
Otsu Method ◽  
Labview Platform ◽  
Dynamic Link

In order to design a wire bonder, a vision position module on LabVIEW platform is needed. In this paper, an improved Otsu method is achieved based on LabVIEW and dynamic-link library (DLL). By analyzing the mechanism of dynamic-link library, this paper introduced the key technique of achieving image segmentation on LabVIEW by using DLL. Finally, experiments are undertaken by using a kind of IC chip. It’s shown that, the quality of resulting images achieved by LabVIEW is similar as that achieved by VC++, and the segmentation costs less than 50ms, about 20ms more than that achieved by VC++.

scholarly journals An Efficient Fuzzy Technique for Detection of Brain Tumor

2013 ◽  
Vol 8 (2) ◽  
pp. 813-818 ◽  
Author(s):  
P.G.K. Sirisha ◽  
C. Naga Raju ◽  
R. Pradeep Kumar Reddy
Keyword(s):  
Image Segmentation ◽  
Brain Tumor ◽  
Medical Image ◽  
Research Field ◽  
Medical Image Segmentation ◽  
Mri Scan ◽  
Innovative Method ◽  
Otsu Method ◽  
The Brain

   In this epoch Medical Image segmentation is one of the most challenging problems in the research field of MRI scan image classification and analysis. The importance of image segmentation is to identify various features of the image that are used for analyzing, interpreting and understanding of images. Image segmentation for MRI of brain is highly essential due to accurate detection of brain tumor. This paper presents an efficient image segmentation technique that can be used for detection of tumor in the Brain. This innovative method consists of three steps. First is Image enhancement to improve the quality of the tumor image by eliminating noise and to normalize the image. Second is fuzzy logic which produce optimal threshold to avoid the fuzziness in the image and makes good regions regarding Image and tumor part of the Image. Third is novel OTSU technique applied for separating the tumor regions in the MRI. This method has produced better results than traditional extended OTSU method.

The Optimal Thresholding Technique for Image Segmentaion Using Fuzzy Otsu Method

2015 ◽  
Vol 4 (3) ◽  
pp. 81
Author(s):  
P. Rambabu ◽  
C. Naga Raju
Keyword(s):  
Image Segmentation ◽  
Threshold Value ◽  
Mean Value ◽  
Low Contrast ◽  
Innovative Method ◽  
Otsu Method ◽  
Tone Color ◽  
S Curve ◽  
Selection Of

<p>Image Segmentation plays a very important role in image processing. The single-mindedness of image segmentation is to partition the image into a set of disconnected regions with the homogeneous and uniform attributes like intensity, tone, color and texture. There are various methods for image segmentation but no method is suitable for low contrast images. In this paper, we are presenting an efficient and optimal thresholding image segmentation technique that can be used to separate the object and background pixels of the image to improve the quality of low contrast images. This innovative method consists of two steps. Firstly fuzzy logics are used to find optimum mean value using S-curve with automatic selection of controlled parameters to avoid the fuzziness in the image. Secondly, the fuzzy logic’s optimal threshold value used in Otsu method to improve the contrast of the image. This method, gives better results than traditional Otsu and Fuzzy logic techniques. The graphs and tables of values show that the proposed method is superior to traditional methods.</p>

Research of Multi-Axes Motion Control System Based on LabVIEW Platform

2012 ◽  
Vol 569 ◽  
pp. 763-768 ◽  
Author(s):  
Lu Hua Deng ◽  
Jun Hui Li ◽  
Ling Gang Liu
Keyword(s):  
Control System ◽  
Motion Control ◽  
Servo Motor ◽  
Dynamic Link Library ◽  
Control Card ◽  
Motion Models ◽  
The Common ◽  
Virtual Platform ◽  
Labview Platform ◽  
Dynamic Link

According to Dynamic Link Library (DLL), the common motion card was successfully run on Labview virtual platform, which can graphically compile program. Based on Labview8.6 platform, Leadtech SMC-6480 control card and Yaskawa SJME-02AMA41 servo motor were used as the hardware to realize multi-axes motion control. The results indicated that each axis has three motion models of automatic, manual and return-to-zero, which can switch mutually at any time.

State-of-the-Art: A Systematic Literature Review on Image Segmentation in Latent Fingerprint Forensics

2019 ◽  
Vol 12 ◽  
Author(s):  
Megha Chhabra ◽  
Manoj Kumar Shukla ◽  
Kiran Kumar Ravulakollu
Keyword(s):  
Image Segmentation ◽  
Background Noise ◽  
State Of The Art ◽  
Recognition Rate ◽  
Poor Quality ◽  
Latent Fingerprint ◽  
In The Beginning ◽  
The Comparative Study ◽  
Finger Skin

: Latent fingerprints are unintentional finger skin impressions left as ridge patterns at crime scenes. A major challenge in latent fingerprint forensics is the poor quality of the lifted image from the crime scene. Forensics investigators are in permanent search of novel outbreaks of the effective technologies to capture and process low quality image. The accuracy of the results depends upon the quality of the image captured in the beginning, metrics used to assess the quality and thereafter level of enhancement required. The low quality of the image collected by low quality scanners, unstructured background noise, poor ridge quality, overlapping structured noise result in detection of false minutiae and hence reduce the recognition rate. Traditionally, Image segmentation and enhancement is partially done manually using help of highly skilled experts. Using automated systems for this work, differently challenging quality of images can be investigated faster. This survey amplifies the comparative study of various segmentation techniques available for latent fingerprint forensics.

Comparison of Thresholding and Edge Detection Segmentation Techniques

2013 ◽  
Vol 860-863 ◽  
pp. 2783-2786
Author(s):  
Yu Bing Dong ◽  
Hai Yan Wang ◽  
Ming Jing Li
Keyword(s):  
Image Segmentation ◽  
Root Mean Square Error ◽  
Edge Detection ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Experimental Results ◽  
Mean Square ◽  
Segmentation Method ◽  
Segmentation Algorithms

Edge detection and thresholding segmentation algorithms are presented and tested with variety of grayscale images in different fields. In order to analyze and evaluate the quality of image segmentation, Root Mean Square Error is used. The smaller error value is, the better image segmentation effect is. The experimental results show that a segmentation method is not suitable for all images segmentation.

The Detection Method of Lane Line Based on the Improved Otsu Threshold Segmentation

2015 ◽  
Vol 741 ◽  
pp. 354-358 ◽  
Author(s):  
Yang Shan Tang ◽  
Dao Hua Xia ◽  
Gui Yang Zhang ◽  
Li Na Ge ◽  
Xin Yang Yan
Keyword(s):  
Image Segmentation ◽  
Processing Time ◽  
Detection Method ◽  
Segmentation Algorithm ◽  
Test Results ◽  
Threshold Segmentation ◽  
Otsu Method ◽  
Time Requirements ◽  
Lane Line ◽  
Center Distance

For overcoming the shortage of Otsu method, proposed an improved Otsu threshold segmentation algorithm. On the basis of Otsu threshold segmentation algorithm, the gray level was divided into two classes according to the image segmentation, to determine the best threshold by comparing their center distance, so as to achieve peak line recognition under the condition of multiple gray levels. Then did experiments on image segmentation of the lane line with MATLAB by traditional Otsu threshold segmentation algorithm and the improved algorithm, the threshold of traditional Otsu threshold segmentation algorithm is 144 and the threshold of the improved Otsu threshold segmentation algorithm is 131, the processing time is within 0.453 s. Test results show that the white part markings appear more, the intersection place of white lines and the background is more clear, so this method can identify lane markings well and meet the real-time requirements.

Development of Parametric CAD System Based on Pro / Toolkit and Database Technology

2011 ◽  
Vol 55-57 ◽  
pp. 2235-2241 ◽  
Author(s):  
Hui Lan Zhou
Keyword(s):  
User Interface ◽  
Dynamic Link Library ◽  
Cad System ◽  
Mechanical Part ◽  
Data Object ◽  
Standard Part Library ◽  
Database Technology ◽  
Parametric Cad ◽  
Developing Method ◽  
Dynamic Link

With Pro/Toolkit of Pro/E and ADO(ActiveX Data Object) database technology, part parametric CAD system is developed and an successful instance is introduced in the paper. In the CAD system, interface between Pro/E and VC++6.0 is created correctly using Pro / Toolkit and user interface for part parametric designing can be achieved by means of dll( dll dynamic link) library built in VC++6.0 .Meanwhile ADO database is applied in the CAD system to manage all part parameters and thus part revising and updating can be realized quickly. The developing method in the CAD system not only is applicable to typical mechanical part designing but also be helpful to establishing standard part library.

scholarly journals Fast Algorithm for Selective Image Segmentation Model

2018 ◽  
Vol 7 (4.33) ◽  
pp. 41
Author(s):  
Abdul K Jumaat ◽  
Ke Chen
Keyword(s):  
Image Segmentation ◽  
Fast Algorithm ◽  
Visual Quality ◽  
Projection Algorithm ◽  
Computational Time ◽  
Segmentation Result ◽  
Numerical Tests ◽  
Specific Object ◽  
The Common

Selective image segmentation model aims to separate a specific object from its surroundings. To solve the model, the common practice to deal with its non-differentiable term is to approximate the original functional. While this approach yields to successful segmentation result, however the segmentation process can be slow. In this paper, we showed how to solve the model without approximation using Chambolle’s projection algorithm. Numerical tests show that good visual quality of segmentation is obtained in a fast-computational time.  

scholarly journals OILSPILL AND LOOK-ALIKE SPOTS FROM SAR IMAGERY USING OTSU METHOD AND ARTIFICIAL NEURAL NETWORK

2020 ◽  
Vol 4 (11) ◽  
pp. 1-10
Author(s):  
M. Sornam
Keyword(s):  
Image Segmentation ◽  
Oil Spill ◽  
Oil Spills ◽  
Marine Ecosystem ◽  
Dark Spot ◽  
Oil Spill Detection ◽  
Otsu Method ◽  
Artificial Neural ◽  
Propagation Network

Oil spill pollution plays a significant role in damaging marine ecosystem. Discharge of oil due to tanker accidents has the most dangerous effects on marine environment. The main waste source is the ship based operational discharges. Synthetic Aperture Radar (SAR) can be effectively used for the detection and classification of oil spills. Oil spills appear as dark spots in SAR images. One major advantage of SAR is that it can generate imagery under all weather conditions. However, similar dark spots may arise from a range of unrelated meteorological and oceanographic phenomena, resulting in misidentification. A major focus of research in this area is the development of algorithms to distinguish ‘oil spills’ from ‘look-alikes’. The features of detected dark spot are then extracted and classified to discriminate oil spills from look-alikes. This paper describes the development of a new approach to SAR oil spill detection using Segmentation method and Artificial Neural Networks (ANN). A SAR-based oil-spill detection process consists of three stages: image segmentation, feature extraction and object recognition (classification) of the segmented objects as oil spills or look-alikes. The image segmentation was performed with Otsu method. Classification has been done using Back Propagation Network and this network classifies objects into oil spills or look-alikes according to their feature parameters. Improved results have been achieved for the discrimination of oil spills and look-alikes.

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