Scene Text Recognition using Artificial Neural Network: A Survey

Abstract

Nowadays, scene text recognition has become an important emerging area of research in the field of image processing. In image processing, character recognition boosts the complexity in the area of Artificial Intelligence. Character recognition is not easy for computer programs in comparison to humans. In the broad spectrum of things, it may consider that recognizing patterns is the only thing which humans can do well and computers cannot. There are many reasons including various sources of variability, hypothesis and absence of hard-and-fast rules that define the appearance of a visual character. Hence; there is an unavoidable requirement for heuristic deduction of rules from different samples. This review highlights the superiority of artificial neural networks, a popular area of Artificial Intelligence, over various other available methods like fuzzy logic and genetic algorithm. In this paper, two methods are listed for character recognition -offline and online. The -Offline‖ methods include Feature Extraction, Clustering, and Pattern Matching. Artificial neural networks use the static image properties. The online methods are divided into two methods, k-NN classifier and direction based algorithm. Thus, the scale of techniques available for scene text recognition deserves an admiration. This review gives a detail survey of use of artificial neural network in scene text recognition.

A Machine-Learning-Based Business Analytical System for Insurance Customer Relationship Management and Cross-Selling

“…Most studies in these fields have suggested that ANNs perform as well as or better than other machine learning/statistical techniques (Wong & Selvi, 1998;Vellido et al, 1999). Current emerging areas in ANN research include image processing, text recognition (Kumar et al, 2016), disease detection (Kirmani & Ansarullah, 2016), and stock market analysis and prediction (Mahendran et al, 2020).…”

Detection and recognition of cursive text from video frames

“…Among handengineered features, popular descriptors investigated for detection of natural scene text include the Scale Invariant Feature Transform (SIFT) [86,87], Strokelets [88], and Histogram of Oriented Gradients (HOG) [89,90], etc. Likewise, ANNs [91][92][93] and SVMs [94,95] have been commonly employed as classifiers. In addition to recognition, techniques based on word spotting have also been investigated on scene text images [96,97].…”

Reliability analysis and optimization of computer communication network based on genetic algorithm

“…The probability value used to determine whether there is an arc is an important basis for generating the initial population. In the experimental design with 10, 20, and 30 nodes, the following standards are systematically set 29 Set the arc probability between (0, 1), which determines whether there is an arc between nodes. Monte Carlo simulation is used to estimate the system reliability of each connected network. Set the probability value of arc and the corresponding network reliability value. …”