Character Segmentation to the Case Study Image of Quadratic Equation Expression

2020 ◽  
Vol 8 (3) ◽  
pp. 285
Author(s):  
Putu Indah Pradnyawati ◽  
I Gede Arta Wibawa
Keyword(s):  
Image Segmentation ◽  
Structural Analysis ◽  
Quadratic Equation ◽  
Character Segmentation ◽  
Connected Component ◽  
Quadratic Equations ◽  
Connected Component Labeling ◽  
Mathematical Expressions ◽  
Basic Numbers

The introduction of digital mathematical expressions can be said to be unusual because mathematical expressions consist of various symbols. The introduction of mathematical expressions can be divided into two main steps, namely the introduction of symbols and structural analysis. Segmentation of an image is an important part in the recognition of handwritten mathematical expressions, because segmentation is the first step of the recognition process. In this study, we will present the process of handwriting image segmentation for mathematical expressions in the form of quadratic equations using the Connected Component Labeling (CCL) method. From the results of the research conducted, it can be concluded that the segmentation process has succeeded in segmenting the handwritten images of mathematical expressions in the form of quadratic equations by producing the characters (compound characters) that make up mathematical expressions and grouping the ranks and basic numbers of quadratic equations.

Hijaiyah Letter Segmentation Using Connected Component Labeling Method

2020 ◽  
Vol 9 (2) ◽  
pp. 249
Author(s):  
Audini Nifira Putri ◽  
I Putu Gede Hendra Suputra
Keyword(s):  
Image Segmentation ◽  
Character Recognition ◽  
Euclidean Distance ◽  
Recognition System ◽  
Main Character ◽  
Connected Component ◽  
Connected Component Labeling ◽  
Segmentation Process ◽  
Labeling Method

Arabic letters or Hijaiyah letters recognition is a challenge in itself because one letter consists of more than one character, namely the main character, companion character such as dots and lines, and punctuation called harakat. The image segmentation process is the most important in a character recognition system because it affects the separation of objects in an image. In this research, Hijaiyah letter segmentation aims to separate the letters according to the character of each letter using the Connected Component Labeling (CCL) method. Merging labels on each character will be done by looking for the Euclidean distance value from adjacent centroids. The experiment succeeded in segmenting each Hijaiyah character with an accuracy value of 86%. 

scholarly journals CHARACTER IMAGE SEGMENTATION OF JAVANESE SCRIPT USING CONNECTED COMPONENT METHOD

2019 ◽  
Vol 12 (2) ◽  
pp. 67
Author(s):  
Yuna Sugianela ◽  
Nanik Suciati
Keyword(s):  
Image Segmentation ◽  
Character Recognition ◽  
Region Of Interest ◽  
Character Segmentation ◽  
Translation System ◽  
Important Process ◽  
Connected Component ◽  
Projection Profile ◽  
Centroid Distance ◽  
Meaningful Word

Automation of Javanese script translation is needed to make it easier for people to understand the meaning of ancient Javanese script. By using Javanese script image as input, the translation system generally consists of character segmentation, character recognition, and combining the recognized characters as a meaningful word. The segmentation which obtains region of interest of each character, is an important process in the translation system. In the previous research, segmentation using projection profile method can separate each character well. The method can overcome characters overlapping, but it still produces truncated characters. In this study, we proposed a new segmentation to reduce the truncated character. The first step of the proposed method is pre-processing that consists of converting input into binary image and cleaning noises. The next step is to determine the connected component labels, which further perform as candidate of characters. Some of the candidates are still represented by more than one labels, so that we need a process to merge the connected component labels that have centroid distance less than threshold. We evaluate the proposed method using Intersection over Union (IoU). The evaluation shows the best accuracy 93,26%.

scholarly journals Boundary Loss-Based 2.5D Fully Convolutional Neural Networks Approach for Segmentation: A Case Study of the Liver and Tumor on Computed Tomography

Algorithms ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 144
Author(s):  
Yuexing Han ◽  
Xiaolong Li ◽  
Bing Wang ◽  
Lu Wang
Keyword(s):  
Image Segmentation ◽  
Spatial Information ◽  
Medical Images ◽  
Tumor Segmentation ◽  
Convolutional Networks ◽  
Learning Framework ◽  
Fully Convolutional Networks ◽  
Segmentation Accuracy ◽  
Boundary Information

Image segmentation plays an important role in the field of image processing, helping to understand images and recognize objects. However, most existing methods are often unable to effectively explore the spatial information in 3D image segmentation, and they neglect the information from the contours and boundaries of the observed objects. In addition, shape boundaries can help to locate the positions of the observed objects, but most of the existing loss functions neglect the information from the boundaries. To overcome these shortcomings, this paper presents a new cascaded 2.5D fully convolutional networks (FCNs) learning framework to segment 3D medical images. A new boundary loss that incorporates distance, area, and boundary information is also proposed for the cascaded FCNs to learning more boundary and contour features from the 3D medical images. Moreover, an effective post-processing method is developed to further improve the segmentation accuracy. We verified the proposed method on LITS and 3DIRCADb datasets that include the liver and tumors. The experimental results show that the performance of the proposed method is better than existing methods with a Dice Per Case score of 74.5% for tumor segmentation, indicating the effectiveness of the proposed method.

Fast connected-component labeling

2009 ◽  
Vol 42 (9) ◽  
pp. 1977-1987 ◽  
Author(s):  
Lifeng He ◽  
Yuyan Chao ◽  
Kenji Suzuki ◽  
Kesheng Wu
Keyword(s):  
Connected Component ◽  
Connected Component Labeling

The Use of Aluminium for Commercial Vehicle Structures—A Feasibility Study

1978 ◽  
Vol 192 (1) ◽  
pp. 81-92
Author(s):  
B. B. Hundy ◽  
S. Broadstock
Keyword(s):  
Structural Analysis ◽  
Aluminium Alloy ◽  
Feasibility Study ◽  
Commercial Vehicle ◽  
Load Capacity ◽  
Typical Case ◽  
Extra Cost ◽  
Manufacturing Processes ◽  
Structural Components

The use of aluminium alloy instead of steel for the structural components of a 32 ton articulated lorry has been examined. The probable manufacturing difficulties have been assessed and shown to be minimal. The savings in weight possible by using aluminium have been calculated from a structural analysis of the cab, tractor chassis and trailer and from this and an assessment of the manufacturing processes the extra cost of manufacturing in aluminium has been determined. A typical case study shows that this extra cost can be easily recovered by utilising the increased load capacity of the vehicle during the first few years of its life.

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