1. Clustering applications would include things like character recognition, sonar / radar signal classification, and robotic control.

2. And character recognition is relatively slow and prone to errors even on powerful computers.

3. Products are available that do character recognition and handwriting analysis, including analysis of complex characters.

4. Parsytec plans to release an entire family of character recognition systems with prices starting at ￡15,000.

5. Further details of printed character recognition systems are not included here in order to concentrate on cursive handwriting systems.

6. The humanoid Chinese character recognition system.

7. In an OCR (Optical Character Recognition) system, character normalization is a crucial step to eliminate variations in character size or position.

8. A novel printed character recognition method based on Degraded Hidden Markov Model is proposed in this dissertation, which can be applied to engineering.

9. A character recognition system for tire code is implemented by the digital image processing technology.

10. One important Hangul character recognition method is thus the approach of separating each grapheme of character and identifying the separated graphemes independently.

11. In character recognition, the inadvertent absence of ink within a character outline.

12. In this paper, a new algorithm of handwritten character recognition is proposed to incr.

13. Multilingual Multimedia Technology and CAI Technology ; Multilingual Character Recognition Systems.

14. In the scan area, optical character recognition ( OCR ) is the most popular businesses a technology.

15. Character recognition module The module consists mainly of handwritten numeral recognition.

16. This could include word processing, a database, case management and optical character recognition.

17. One example is the method of recognition using template matching which is applied in both speech recognition and optical character recognition.

18. All permutations of transitional probabilities arising out of the character recognition are calculated to give an associated probability for a given string.

19. The Ni1000 can be combined with a personal computer for fast character recognition, Intel says.

20. This can be on-line or off-line recognition of hand-printed characters, or of machine-printed characters using optical character recognition.

21. Typically context is used only in the form of spelling correction information to compensate for errors in character recognition.

22. To treat the random of a character's direction, the method of character recognition based on annual ring is given.

23. With the progress of computer science, image processing and character recognition, it has been possible for us using computer to identify the information in ID card image automatically.

24. This paper briefly introduces the flying spot scanner of the "789" model of Optical Character Recognition system developed in Futan University.

25. It is proved that this algorithm can be used to recognize varisized characters with high tolerance to distortion and blur(), and its character recognition accuracy is above 94%.

26. This segmentation algorithm that has promising results (the segmentation correct rate reach to 86.3%) and is then incorporated into a complete bank check character recognition system.

27. It is the key to solve the problems such as face identification and handwritten character recognition.

28. Practice in handwritten numeral recognition and off line handwritten Chinese character recognition strongly supports the ideas and the methods.

29. Based on eight shape code scheme and code - extraction algorithm, humanoid Chinese character recognition system is presented.

30. It consists of image display, image conversion, image processing, character recognition, and help to a few other components.

31. This paper is to introduce designing principle and managing software of printed Chinese character recognition unit that consists of 16-bit CPU, dynamic RAM array, training and sorting logic etc.

32. The paper presents a fast hand-written digital character recognition method based on global feature(convex and concave feature)via simulating the process of human's eyes' recognition.

33. Owing to the effect of the high temperature, complex illumination and bad-imaging environment, there are a lot of difficulties in real-time automatic character recognition at ends of steel billet.

34. Document analysis and understanding is important part of OCR ( Optical Character Recognition ) system.

35. A fuzzy gradient feature extraction method based on gradient normalization applied in handwritten character recognition is proposed.

36. Offline Character Recognition for The template matching, USPS font terminology Fisher Linear found handwritten identification numbers.

37. A novel printed character recognition method based on degraded Hidden Markov Model(DHMM) is(proposed, ) which can be applied to engineering.

38. Magnetic ink character recognition (MICR): Devices which can identify characters printed in magnetic ink and convert them into digital data.

39. Character recognition: Reading characters by machine, often for digital storage.

40. The problem of Chinese handwritten character recognition by computer is thought of one of the most difficult problems in the field of pattern recognition.

41. This paper describes the handwritten character recognition of the three processes, including image pre-processing, extraction and Signature BP neural network classifiers.

42. To fulfill the application requirement of character recognition in image, an improved algorithm for contour following algorithm was proposed and a contour list based on chain code was presented.

43. The key of Off - line handwritten character recognition are feature extract and classifier design.

44. Handwritten numeral recognition is a hotspot of study for years, and is some especial issue of character recognition.

45. In order to improve the recognition performance of synergetic neural network further, a hierachical synergetic neural network model for multifont character recognition was proposed.

46. Graphic character recognition ( OCR ) is a common thing.

47. With the development of computer technology, a new input method named on - line handwritten Chinese character recognition appears.

48. Feature extraction is the key part of handwritten chinese character recognition.

49. It proves effective and efficient for printed character recognition in the high noise level environment.

50. The history of off-line character recognition is first systematically summarized, focusing on the upgrade of the recognition unit .

51. The productions of some ethnological character recognition have been transformed into commercial software, but the research on the recognition of Mongolian characters is now just beginning.

52. With the rapid development of OCR technology, the printed character recognition technology has been mature and applied widely.

53. This paper introduces the general steps of Digital Character Recognition. In accordance with the steps we located and splited characters of the images with Projection Method, and thin the characters.

54. Digital Character Recognition is the main goal of the system, which automatically identify the pre-processed image.

55. Handwritten character recognition is one of the research topic field of image processing and pattern recognition.

56. Optical character recognition ( OCR ) is one of the most successful applications of pattern recognition.

57. Being a special computer vision system in the real-time case, the LPR system mainly includes the subsystem of license plate detection and character recognition.

58. In developing the multi-fonts Chinese character recognition system by structural approach, the stroke extraction is an important problem.

59. A multifont printed character recognition based on floating mask method and neural network is presented in this paper.

60. Include: neural networks, handwriting character recognition, fingerprint recognition, voice recognition, face recognition, expert systems.

61. In this paper, the ancient Chinese character recognition image classification system is developed. The results show that the system has high classification ability.

62. The character recognition threshold or acuity of Chinese characters was measured and compared with English letters and optotype E, by the method of constant stimuli.

63. Optical character recognition, usually abbreviated to OCR, is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text.

64. Feature extraction is the difficulty of handwritten chinese character recognition.

65. Being a special computer vision system in the real-time case, the LPR (License Plate Recognition) system mainly includes the subsystem of license plate detection and character recognition.

66. The minimum distance classification has been broadly applied to the areas of character recognition and image recognition.

67. At present(), an emphasis of the research is put on unconstrained handwritten character recognition.

68. In optical character recognition, the insufficient horizontal spacing between characters.

69. Optical character recognition OCR is the core of DIA, dealing with either printed or handwritten document.

70. Offline machine printed character recognition, an important branch of pattern recognition, is one of the vitalest parts of intelligent interface.

71. This paper aims to study the processing methods and algorithms to be improved in certain stages of the process of handwritten character recognition.

72. His credentials stem from being a pioneer in various fields of computing, such as optical character recognition – the technology behind CDs – and automatic speech recognition by machine.

73. In this paper, we discuss a new method to effectively improve offline handwritten character recognition through semantic analysis.

74. Hence, improve the correct rate of off - line handwritten Chinese character recognition.

75. OCR ( Optical Character Recognition ) is an important branch of pattern recognition.

76. In character recognition, a straight line or arc used as a segment of a graphic character.