Emergence networks mimics biological nervous system unleash generations of inventions and discoveries in the artificial intelligent field. These networks have been introduced by McCulloch and Pitts and called neural networks. Neural network’s function is based on principle of extracting the uniqueness of patterns through trained machines to understand the extracted knowledge. Indeed, they gain their experiences from collected samples for known classes (patterns). Quick development of neural networks promotes concept of the pattern recognition by proposing intelligent systems such as handwriting recognition, speech recognition and face recognition. In particular, Problem of handwriting recognition has been considered significantly during the last decades in the academic and industrial fields by employing types of direct matching. Performance of this recognition has been paying strong attention through developing several schemas and algorithms to learn the machines. In the light of that development, David Shepard invented first modern OCR’s version to read texts in 1951. After few years, this innovation is followed by originating a prototype machine to read upper case characters with speed of a character per minutes (Srihari & Lam 1995).In the same way, many companies, such as IBM, have continued in developing reader systems to challenge problems of character recognition(Lianwen, Kwokping & Bingzheng 1995). The competition between the realised systems concentrated on improving accuracy and speed of the intelligent machine.
Later, Brown, Fay & Walker (1988) introduced a simple system to recognise handwritten numerals by using geometrical and local measurements. Following this further, Suen et al. (1992) acknowledge that handwriting r...
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...ing Gradient and Curvature of Gray Scale Image', Patter Recognition vol. 35, no. 10, pp. 2051-9.
Srihari, S.N. & Lam, S.W. 1995, Character Recognition, CEDAR-TR-95-1.
Suen, C.Y., Legault, R., Nadal, C., Cheriet, M. & Lam, L. 1993, 'Building a new generation of handwriting recognition system', Pattern Recognition Letters, vol. 1.14, no. 4, pp. 303 - 15.
Suen, C.Y., Nadal, C., Legault, R., Mai, T.A. & Lam, L. 1992, 'Computer Recognition of Unconstrained Handwritten Numerals', paper presented to the Proceedings of the IEEE.
Teow, L.N. & Loe, K.F. 2002, 'Robust Vision-Based Feature and Classification Schemes for Off-Line Handwritten Digit Recognition', Pattern Recognition vol. 35, no. 1, pp. 2355-64.
Zhang, P. 2006, 'Reliable Recognition of Handwritten Digits Using A Cascade Ensemble Classifier System and Hybrid Features', Concordia University, Montreal, Quebec, Canada.
Kutcher claims, “We haven’t lost romance in the digital age, but we may be neglecting it, in doing so, acquainted art forms are taking on new importance. The power of a handwritten letter is greater than ever. It’s personal and deliberate and means more than e-mail or text ever will. ’’(96)Handwriting is different and unique for each individual. You can look at the letter and judge how much effort a person put into writing it.
With the swarm of technology, handwriting, a vital skill, may be on the brink of extinction, despite that it is able to create a “model citizen, assimilate immigrants, and even reform juvenile delinquents” (Korper). Believe it or not: handwriting is important. However, the debate about handwriting is still questionable. Handwriting allows for effective memory retention and is an significant and unique action to develop certain regions of your brain (Grossberg). However, handwriting is also outdated and lacks the agility of the keyboard (Korper). Nonetheless, some of these positive aspects of handwriting are largely due to the ‘drill’ factor emphasized in the Palmer Method of handwriting used present day (Korper).
Biometrics-based authentication applications include workstation, network, and domain access, single sign-on, application logon, data protection, remote access to resources, transaction security and Web security (Campbell, 1995). Utilized alone or integrated with other technologies such as smart cards, encryption keys and digital signatures, biometrics are set to pervade nearly all aspects of the economy and our daily lives (Campbell, 1995). Among the features measured are; face, fingerprints, hand geometry, iris, and voice (Campbell, 1995).
4.5 Appling Optical Character Recognition (OCR) to a scanned PDF document to make it text searchable (optional)
Handwriting is an important part of education. Many states require essay tests in which content is more important than handwriting or even spelling. But those essays still need to be legib...
...ge flow and pattern types, are prominent enough to align fingerprints directly. Nilsson [26] detected the core point by complex filters applied to the orientation field in multiple resolution scales, and the translation and rotation parameters are simply computed by comparing the coordinates and orientation of the two core points. Jain [27] predefined four types of kernel curves:first is arch, second is left loop ,third is right loop and fourth is whorl, each with several subclasses respectively. These kernel curves were fitted with the image, and then used for alignment. Yager [28] proposed a two stage optimization alignment combined both global and local features. It first aligned two fingerprints by orientation field, curvature maps and ridge frequency maps, and then optimized by minutiae. The alignment using global features is fast but not robust, because the
describes the Contourlet transform and rotation-scale invariant texture representation. Section 4 contains the description of similarity measure for image retrieval. Simulation results in Section 5 will show the performance of our scheme. Finally,Section 6 concludes this presentation.
Biometrics is described as the use of human physical features to verify identity and has been in use since the beginning of recorded history. Only recently, biometrics has been used in today’s high-tech society for the prevention of identity theft. In this paper, we will be understanding biometrics, exploring the history of biometrics, examples of today’s current technology and where biometrics are expected to go in the future.
From many points of views, it can be considered as the starting point. The team working with it has a dream to make more objects recognition which is context base. They also have a desire to make the recognition more interactive. A new and exceptional feature has been suggested where a particular part of an image can be tapped and the information can be heard.
[4] Borut Batagelj, (May 2006). Face recognition in different subspaces - A comparative study”, 6th International Workshop on Pattern Recognition in Information Systems, PRIS 2006 in conjunction with ICEIS 2006, Paphos, Cyprus.
With the growing demand for electronic documentation and paperless business solutions – there has been a significant growth in interest surrounding OCR technology. Unfortunately, despite its increase in popularity and numerous benefits to traditional scanning, many professionals are still left with the question - what is OCR?
Artificial neural networks are systems implemented on computer systems as specialized hardware or sophisticated software that loosely model the learning and remembering functions of the human brain. They are an attempt to simulate the multiple layers of processing elements in the brain, called neurons. These elements are implemented in such a way so that the layers can learn from prior experience and remember their outputs. In this way, the system can learn to recognize certain patterns and situations and apply these to certain priorities and output appropriate results. These types of neural networks can be used in many important situations such as priority in an emergency room, for financial assistance, and any type of pattern recognition such as handwritten or text-to-speech recognition.
As the late 1800’s came around, a man named Herman Hollerith developed a computing machine that can read into punched cards.
Artificial Intelligence is the scientific theory to advance the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines. This is going to hold the key in the future. It has always fa...
Handwritten signatures happens in different patterns and there is a great deal of dissimilarity signatures of people even of the same area with same language. Some used to just write their name while others follow certain pattern to represent their signature. Signatures done with complexity are however less vulnerable to forgery effects [7]. Also, the signatures are very much influenced by the thinking panorama of a person. There is a particular process on how a signature s generated. Signature has three attributes at minimum . They are pattern form, movement and variation, and since the signatures are produced by moving a pen on a paper, movement of pattern is the most important