LOCATING TEXT IN IMAGES BASED ON THE SMOOTH GRAY-LEVEL DETECTION

2012 ◽  
Vol 12 (04) ◽  
pp. 1250027 ◽  
Author(s):  
SHIUENG-BIEN YANG ◽  
CHI-FENG WU
Keyword(s):  
Experimental Results ◽  
New Method ◽  
Gray Level ◽  
Geometrical Structures ◽  
Text Extraction ◽  
Highly Effective ◽  
Better Than

The morphological technique is widely used for text extraction from images. It is highly effective in extracting geometrical structures and representing shapes in images. However, the morphological technique does not consider the variance of gray levels between neighboring pixels in images. Generally in images, changes in gray levels between neighboring nontext pixels are smoother than those between neighboring text pixels. This paper, therefore, proposes a new method for locating text based on the smooth gray-level detection. Experimental results reveal that the proposed method locates text in images better than other methods.

Study on Methods for Improving LMD End Effect

2016 ◽  
Vol 851 ◽  
pp. 559-566
Author(s):  
Feng Wei Wang ◽  
Yun Qi Zhou ◽  
Shi Jian Zhou
Keyword(s):  
Single Component ◽  
Experimental Results ◽  
New Method ◽  
End Effect ◽  
End Effects ◽  
Physical Sense ◽  
Stationary Signals ◽  
Better Than ◽  
Self Adaptive

The LMD is a new method for analyzing non-stationary signals. It can decompose complicated signals into a set of single-component signals, each of which has physical sense. But peforming the LMD will produce end effects which make results distortion. After analyzing the reasons for these, the ariticle takes adcantage of three normal methods to overcome the end effects of LMD. Experimental results of three models showed that the method of self-adaptive waveform matching was better than other methods.

scholarly journals Using Qualitative Hypotheses to Identify Inaccurate Data

1995 ◽  
Vol 3 ◽  
pp. 119-145 ◽  
Author(s):  
Q. Zhao ◽  
T. Nishida
Keyword(s):  
Infrared Spectra ◽  
Difficult Problem ◽  
Experimental Results ◽  
New Method ◽  
Coefficient Function ◽  
Related Data ◽  
Inaccurate Data ◽  
Practical System ◽  
Dynamic Shift ◽  
Better Than

Identifying inaccurate data has long been regarded as a significant and difficult problem in AI. In this paper, we present a new method for identifying inaccurate data on the basis of qualitative correlations among related data. First, we introduce the definitions of related data and qualitative correlations among related data. Then we put forward a new concept called support coefficient function (SCF). SCF can be used to extract, represent, and calculate qualitative correlations among related data within a dataset. We propose an approach to determining dynamic shift intervals of inaccurate data, and an approach to calculating possibility of identifying inaccurate data, respectively. Both of the approaches are based on SCF. Finally we present an algorithm for identifying inaccurate data by using qualitative correlations among related data as confirmatory or disconfirmatory evidence. We have developed a practical system for interpreting infrared spectra by applying the method, and have fully tested the system against several hundred real spectra. The experimental results show that the method is significantly better than the conventional methods used in many similar systems.

A Joint Method Based on Wavelet and Curvelet Transform for Image Denoising

2012 ◽  
Vol 532-533 ◽  
pp. 758-762
Author(s):  
Hua Wang ◽  
Jian Zhong Cao ◽  
Li Nao Tang ◽  
Zuo Feng Zhou
Keyword(s):  
Wavelet Transform ◽  
Image Denoising ◽  
High Frequency ◽  
Curvelet Transform ◽  
Experimental Results ◽  
New Method ◽  
Good Effect ◽  
Noisy Image ◽  
Joint Method ◽  
Better Than

Wavelet transform is widely used and has good effect on image denoising. Wavelet transform has unique advantages in dealing with the smooth area of image but is not so perfect in high frequency areas such as the edges. However, curvelet transform can supply this gap when dealing with the high frequency areas because of the characteristic of anisotropy. In this paper, we proposed a new method which is based on the combination of wavelet transform and curvelet transform. Firstly, we detected the edges of the noisy-image using wavelet transform. Based on the edges we divided the image into two parts: the smoothness and the edges. Then, we used different transform methods to dispose different areas of the image, wavelet threshold denoising is used in smoothness while FDCT denoising is used in edges. Experimental results showed that we could get better visual effect and higher PSNR, which indicated that the proposed method is better than using wavelet transform or curvelet transform respectively.

scholarly journals Gray Level Image Threshold Using Neutrosophic Shannon Entropy

2019 ◽  
Author(s):  
Vasile Patrascu
Keyword(s):  
Shannon Entropy ◽  
Experimental Results ◽  
New Method ◽  
Gray Level ◽  
Segmentation Method ◽  
Separation Threshold ◽  
Multiple Thresholds ◽  
Gray Level Image ◽  
Information Components ◽  
Grayscale Images

This article presents a new method of segmenting grayscale images by minimizing Shannon's neutrosophic entropy. For the proposed segmentation method, the neutrosophic information components, i.e., the degree of truth, the degree of neutrality and the degree of falsity are defined taking into account the belonging to the segmented regions and at the same time to the separation threshold area. The principle of the method is simple and easy to understand and can lead to multiple thresholds. The efficacy of the method is illustrated using some test gray level images. The experimental results show that the proposed method has good performance for segmentation with optimal gray level thresholds.

THE SOURCES OF AUXIN HORMONE TO GROWTH OF SHOOT PINEAPPLE STEM CUTTING (Ananascomosus.L. Merr.)

2016 ◽  
Vol 1 (1) ◽  
pp. 45-52
Author(s):  
Palupi Puspitorini
Keyword(s):  
Water Concentration ◽  
Urine Concentration ◽  
Experimental Results ◽  
Stem Cuttings ◽  
Randomized Design ◽  
Natural Hormone ◽  
Cow Urine ◽  
Urine Concentrations ◽  
Completely Randomized Design ◽  
Better Than

The aim of this study was to select the best sources of auxin of which it can stimulate the growth of shoots Pineapple plant cuttings. This research is compiled in a completely randomized design (CRD) with 4 treatments and 6 replications. The Data were statistically Analyzed by the DMRT. Level of treatment given proves that no treatment 0%, cow urine concentration of 25%, young coconut water concentration of 25% and Rootone F 100 mg / cuttings. The results showed that cow urine concentrations of 25% and Rootone F 100 mg give the best results in stimulating the growth of shoots pineapple stem cuttings. Experimental results concluded that the effect of this natural hormone were better than the shoots without given hormone.           

A Computational Method for the Identification of Endolysins and Autolysins

2020 ◽  
Vol 27 (4) ◽  
pp. 329-336 ◽  
Author(s):  
Lei Xu ◽  
Guangmin Liang ◽  
Baowen Chen ◽  
Xu Tan ◽  
Huaikun Xiang ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Cell Wall ◽  
Experimental Results ◽  
Computational Method ◽  
Lytic Enzyme ◽  
Support Vector ◽  
Lytic Enzymes ◽  
Data Set ◽  
Optimal Feature ◽  
Better Than

Background: Cell lytic enzyme is a kind of highly evolved protein, which can destroy the cell structure and kill the bacteria. Compared with antibiotics, cell lytic enzyme will not cause serious problem of drug resistance of pathogenic bacteria. Thus, the study of cell wall lytic enzymes aims at finding an efficient way for curing bacteria infectious. Compared with using antibiotics, the problem of drug resistance becomes more serious. Therefore, it is a good choice for curing bacterial infections by using cell lytic enzymes. Cell lytic enzyme includes endolysin and autolysin and the difference between them is the purpose of the break of cell wall. The identification of the type of cell lytic enzymes is meaningful for the study of cell wall enzymes. Objective: In this article, our motivation is to predict the type of cell lytic enzyme. Cell lytic enzyme is helpful for killing bacteria, so it is meaningful for study the type of cell lytic enzyme. However, it is time consuming to detect the type of cell lytic enzyme by experimental methods. Thus, an efficient computational method for the type of cell lytic enzyme prediction is proposed in our work. Method: We propose a computational method for the prediction of endolysin and autolysin. First, a data set containing 27 endolysins and 41 autolysins is built. Then the protein is represented by tripeptides composition. The features are selected with larger confidence degree. At last, the classifier is trained by the labeled vectors based on support vector machine. The learned classifier is used to predict the type of cell lytic enzyme. Results: Following the proposed method, the experimental results show that the overall accuracy can attain 97.06%, when 44 features are selected. Compared with Ding's method, our method improves the overall accuracy by nearly 4.5% ((97.06-92.9)/92.9%). The performance of our proposed method is stable, when the selected feature number is from 40 to 70. The overall accuracy of tripeptides optimal feature set is 94.12%, and the overall accuracy of Chou's amphiphilic PseAAC method is 76.2%. The experimental results also demonstrate that the overall accuracy is improved by nearly 18% when using the tripeptides optimal feature set. Conclusion: The paper proposed an efficient method for identifying endolysin and autolysin. In this paper, support vector machine is used to predict the type of cell lytic enzyme. The experimental results show that the overall accuracy of the proposed method is 94.12%, which is better than some existing methods. In conclusion, the selected 44 features can improve the overall accuracy for identification of the type of cell lytic enzyme. Support vector machine performs better than other classifiers when using the selected feature set on the benchmark data set.

A Design of High-Accuracy Displacement Measurement Instrument from Principles of Optics

2012 ◽  
Vol 170-173 ◽  
pp. 2924-2928
Author(s):  
Sheng Biao Chen ◽  
Yun Zhi Tan
Keyword(s):  
Measurement Instrument ◽  
High Accuracy ◽  
Mechanical Tests ◽  
Total Reflection ◽  
Displacement Measurement ◽  
New Method ◽  
Water Volume ◽  
Water Drainage ◽  
Accuracy Of Measurement ◽  
Better Than

In order to measure the water drainage volume in soil mechanical tests accurately, it develop a new method which is based on principles of optics. And from both physical and mathematic aspects, it deduces the mathematic relationship between micro change in displacement and the increment projected on screen. The result shows that total reflection condition is better than refraction condition. What’s more, the screen could show the water volume micro variation clearly, so it can improve the accuracy of measurement.

A new method for monitoring the redox potential of fuel salt based on the deposition of 95Nb on Hastelloy C276

2021 ◽  
Vol 109 (5) ◽  
pp. 357-365
Author(s):  
Zhiqiang Cheng ◽  
Zhongqi Zhao ◽  
Junxia Geng ◽  
Xiaohe Wang ◽  
Jifeng Hu ◽  
...  
Keyword(s):  
Redox Potential ◽  
Molten Salt ◽  
Specific Activity ◽  
Chemical Reduction ◽  
Quantitative Approach ◽  
Experimental Results ◽  
New Method ◽  
Molten Salt Reactor ◽  
Fuel Salt ◽  
Well Correlation

Abstract To develop the application of 95Nb as an indicator of redox potential for fuel salt in molten salt reactor (MSR), the specific activity of 95Nb in FLiBe salt and its deposition of 95Nb on Hastelloy C276 have been studied. Experimental results indicated that the amount of 95Nb deposited on Hastelloy C276 resulted from its chemical reduction exhibited a positive correlation with the decrease of 95Nb activity in FLiBe salt and the relative deposition coefficient of 95Nb to 103Ru appeared a well correlation with 95Nb activity in FLiBe salt. Both correlations implied that the measurement of 95Nb activity deposited on Hastelloy C276 specimen might provide a quantitative approach for monitoring the redox potential of fuel salt in MSR.

Devanagari Text Detection From Natural Scene Images

2020 ◽  
Vol 10 (3) ◽  
pp. 44-59
Author(s):  
Sankirti Sandeep Shiravale ◽  
R. Jayadevan ◽  
Sanjeev S. Sannakki
Keyword(s):  
Edge Detection ◽  
Image Understanding ◽  
Text Detection ◽  
Experimental Results ◽  
Combined Approach ◽  
Natural Scene ◽  
Light Conditions ◽  
The Individual ◽  
Natural Scene Images ◽  
Better Than

Text present in a camera captured scene images is semantically rich and can be used for image understanding. Automatic detection, extraction, and recognition of text are crucial in image understanding applications. Text detection from natural scene images is a tedious task due to complex background, uneven light conditions, multi-coloured and multi-sized font. Two techniques, namely ‘edge detection' and ‘colour-based clustering', are combined in this paper to detect text in scene images. Region properties are used for elimination of falsely generated annotations. A dataset of 1250 images is created and used for experimentation. Experimental results show that the combined approach performs better than the individual approaches.

Screening of Coagulant for Washing Wastewater Treatment

2015 ◽  
Vol 1092-1093 ◽  
pp. 972-975
Author(s):  
Jing Yang
Keyword(s):  
Wastewater Treatment ◽  
Removal Rate ◽  
Experimental Results ◽  
The Other ◽  
Aluminium Chloride ◽  
Coagulation Tests ◽  
Cyclic Utilization ◽  
Washing Wastewater ◽  
Better Than

According to the problems exist in cyclic utilization of washing wastewater, the coagulation tests utilizing ferric trichloride (FeCl3), alums, poly aluminium chloride (PAC) and polyacrylamide (PAM) are studied, respectively. Experimental results show that PAC was much better than the other coagulants in the removal of LAS and chroma as a single coagulant. Cast 2.5mL PAC(10%) into quantitative washing wastewater, the removal rate of LAS and chroma reach 82.5% and 87.8%, respectively. When mix the every two kinds of coagulants, maintaining the same total amount of coagulant to 2.5mL, cast1.0mL PAC(10%) and 1.5mL alum (10%) into washing wastewater ,the removal rate of LAS and chroma reach 84.1% and 90.0%, respectively.

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