A Study on Various Techniques Involved in Gender Prediction System: A Comprehensive Review

1. Boyadzhieva, D., G. Gluhchev. A Combined Method for On-Line Signature Verification. – Cybernetics and Information Technologies, Vol. 14, 2014, No 2, pp. 92-97.10.2478/cait-2014-0022Search in Google Scholar

2. Dafe, S. G., S. S. Chavhan. Optical Character Recognition Using Image Processing. – IRJET, Vol. 5, 2018, Isue 3, pp. 962-964.Search in Google Scholar

3. Kaur, S. Gurmukhi Printed Character Recognition Using Hierarchical Centroid Method and SVM. – International Journal of Computer Applications, Vol. 149, 2016, No 3, pp. 24-27.10.5120/ijca2016911367Search in Google Scholar

4. Sharma, A., S. Khare, S. Chavan. A Review on Handwritten Character Recognition. – IJCST, Vol. 8491, 2017, Issue 1, pp. 71-75.Search in Google Scholar

5. Fakhr, M. W. Arabic Optical Character Recognition (OCR). – Systems Overview, Vol. 2011, January 2011.Search in Google Scholar

6. Rubeena, L. R. B. A Comprehensive Study on Handwritten Character Recognition System. – IOSR Journal of Computer Engineering Ver. IV, Vol. 17, 2015, No 2, pp. 2278-661.Search in Google Scholar

7. Yadav, P. Handwriting Recognition System – A Review. – International Journal of Computer Applications, Vol. 114, 2015, No 19, pp. 36-40.Search in Google Scholar

8. Goldberg, L. R., D. Sweeney, P. F. Merenda, J. E. Hughes. Demographic Variables and Personality: The Effects of Gender, Age, Education, and Ethnic/racial Status on Self-Descriptions of Personality Attributes. – Person. Individ. Diff., Vol. 24, 1998, No 3, pp. 393-403.10.1016/S0191-8869(97)00110-4Search in Google Scholar

9. Liwicki, M., A. Schlapbach, P. Loretan, H. Bunke. Automatic Detection of Gender and Handedness from On-Line Handwriting. – Journal of Social Psychology, 2007, No March, pp. 179-183.Search in Google Scholar

10. Liwicki, M., A. Schlapbach, H. Bunke. Automatic Gender Detection Using On-Line and Off-Line Information. – Pattern Analysis and Applications, Vol. 14, 2011, No 1, pp. 87-92.10.1007/s10044-010-0178-6Search in Google Scholar

11. Xie, Q., Q. Xu. Gender Prediction from Handwriting. – Data Mining Course Project. – Fall 2013. 2013, pp. 10-13.Search in Google Scholar

12. Ahmed, M., A. Ghulam, H. Afzal, I. Siddiqi. Improving handwriting Based Gender Classification Using Ensemble Classifiers. – Expert Systems with Applications, Vol. 85, 2017, pp. 158-168.10.1016/j.eswa.2017.05.033Search in Google Scholar

13. Marti, U. V., H. Bunke. The IAM-Database: An English Sentence Database for Off-line Handwriting Recognition. – International Journal on Document Analysis and Recognition, Vol. 5, 2003, No 1, pp. 39-46.10.1007/s100320200071Search in Google Scholar

14. Sokic, E., A. Salihbegovic, M. Ahic-Djokic. Analysis of Off-Line Handwritten Text Samples of Different Gender Using Shape Descriptors. – In: IX International Symposium on Telecommunications (BIHTEL), 2012, pp. 1-6.10.1109/BIHTEL.2012.6412086Search in Google Scholar

15. Al Maadeed, S., W. Ayouby, A. Hassaïn e, J. Mohamad Aljaam. QUWI: An Arabic and English Handwriting Dataset for Offline Writer Identification. – In: IIEEE International Conference on Frontiers in Handwriting Recognition QUWI, Vol. 95, 2012, No 15, pp. 742-747.10.1109/ICFHR.2012.256Search in Google Scholar

16. Hassaïne, A., S. Al Maadeed, J. Aljaam, A. Jaoua. ICDAR2013 – Competition on Gender Prediction from Handwriting. 2013.10.1109/ICDAR.2013.286Search in Google Scholar

17. Al Maadeed, S., A. Hassaine. Automatic Prediction of Age, Gender, and Nationality in Off-line Handwriting. – Eurasip Journal on Image and Video Processing, 2014, pp. 1-10.10.1186/1687-5281-2014-10Search in Google Scholar

18. Siddiqi, I., C. Djeddi, A. Raza. Automatic Analysis of Handwriting for Gender Classification. – Pattern Analysis and Applications, Vol. 18, 2015, No 4, pp. 887-899.10.1007/s10044-014-0371-0Search in Google Scholar

19. Djeddi, C., A. Gattal, L. Souici-Meslati, I. Siddiqi, Y. Chibani, H. El Abed. LAMIS-MSHD: A Multi-Script Offline Handwriting Database. – In: Proc. of International Conference on Frontiers in Handwriting Recognition (ICFHR’14), Vol. 2014, December 2014, pp. 93-97.10.1109/ICFHR.2014.23Search in Google Scholar

20. Bouadjenek, N., H. Nemmour, Y. Chibani. HOG and LBP Features for Writer’s Gender Classification. – International Conference on Electrical Engineering and Control Applications, 2016, pp. 317-325.10.1007/978-3-319-48929-2_24Search in Google Scholar

21. Bouadjenek, N. H. N., Y. C. Age. Gender and Handedness Prediction from Handwriting Using Gradient Features. – Complexity, 2015, pp. 1116-1120.10.1109/ICDAR.2015.7333934Search in Google Scholar

22. Mahmoud, S. A., I. Ahmad, M. Alshayeb, W. G. Al-Khatib, T. U. Braunschweig, S. A. Mahmoud, I. Ahmad, M. Alshayeb, W. G. Al-Khatib, M. T. Parvez, G. A. Fink, V. Margner, H. E. Abed. KHATT: Arabic Off-line Handwritten Text Database. – In: International Conference on Frontiers in Handwriting Recognition (ICFHR’12), 2012, pp. 449-454.10.1109/ICFHR.2012.224Search in Google Scholar

23. Mahmoud, S. A., I. Ahmad, W. G. Al-Khatib, M. Alshayeb, M. Tanvir Parvez, V. Märgner, G. A. Fink. KHATT: An Open Arabic Off-line Handwritten Text Database. – Pattern Recognition, Vol. 47, 2014, No 3, pp. 1096-1112.10.1016/j.patcog.2013.08.009Search in Google Scholar

24. Mirza, A., M. Moetesum, I. Siddiqi, C. Djeddi. Gender Classification from Off-line Handwriting Images Using Textural Features. – In: Proc. of International Conference on Frontiers in Handwriting Recognition, ICFHR, 2017, pp. 395-398.10.1109/ICFHR.2016.0080Search in Google Scholar

25. Gattal, A., C. Djeddi, I. Siddiqi, Y. Chibani. Gender Classification from Offline Multi-Script Handwriting Images Using Oriented Basic Image Features (oBIFs). – Expert Systems with Applications, Vol. 99, 2018, No February, pp. 155-167.10.1016/j.eswa.2018.01.038Search in Google Scholar

26. Grewal, P. K., D. Prashar. Behavior Prediction through Handwriting Analysis. – InternatIonal Journal of Computer Science and Technology, Vol. 3, 2012, No 2, pp. 520-523.Search in Google Scholar

27. Rizvi, F. Personality Prediction through Offline Handwriting Analysis. 2017, No February.Search in Google Scholar

28. Tett, R. P., C. A. Palmer. The Validity of Handwriting Elements in Relation to Self-Report Personality Trait Measures. – Personality and Individual Differences, Vol. 22, 1997, No 1, pp. 11-18.10.1016/S0191-8869(96)00183-3Search in Google Scholar

29. Warner, R. M., D. B. Sugarman. Attributions of Personality Based on Physical Appearance, Speech, and Handwriting. Vol. 50, 1986, No 4, pp. 792-799.10.1037/0022-3514.50.4.792Search in Google Scholar

30. Burr, V. Judging Gender from Samples of Adult Handwriting: Accuracy and Use of Cues. – Journal of Social Psychology, Vol. 142, 2002, No 6.10.1080/0022454020960392912450344Search in Google Scholar

31. Rubin, D. L., K. Greene. Gender-Typical Style in Written Language. – Source: Research in the Teaching of English, Vol. 26, 1992, No 1, pp. 7-40.Search in Google Scholar

32. Koppel, M., S. Argamon, S. A. Rachel. Automatically Categorizing Written Texts by Author Gender. – Literary and Linguistic Computing, Vol. 17, 2002, No 4, pp. 401-412.10.1093/llc/17.4.401Search in Google Scholar

33. Marti, U.-V., H. Bunke. A Full English Sentence Database for Off-Line Handwriting Recognition. – Icdar, Vol. 1999, pp. 705-708.10.1109/ICDAR.1999.791885Search in Google Scholar

34. Bangare, S. L., A. Dubal, P. S. Bangare, D. S. T. P. Reviewing Otsu’s Method for Image Thresholding. – International Journal of Applied Engineering Research, Vol. 10, 2015, No August 2016, pp. 21777-21783.10.37622/IJAER/10.9.2015.21777-21783Search in Google Scholar

35. Jaeger, S., S. Manke, J. Reichert, A. Waibel. On-line Handwriting Recognition: The NPen ++ Recognizer. – Int. J. Doc. Anal. Recognit., March 2001, No May 2017, pp. 169-180.10.1007/PL00013559Search in Google Scholar

36. Al-Maadeed, S., A. Hassaine, A. Bouridane, M. A. Tahir. Novel Geometric Features for Off-Line Writer Identification. – Pattern Analysis and Applications, Vol. 19, 2016, No 3, pp. 699-708.10.1007/s10044-014-0438-ySearch in Google Scholar

37. Koppenhaver, K. M. Forensic Document Examination: Principles and Practice. – Forgery, 2007, pp. 55-60.Search in Google Scholar

38. Siddiqi, I., N. Vincent. Text Independent Writer Recognition Using Redundant Writing Patterns with Contour-Based Orientation and Curvature Features. – Pattern Recognition, Vol. 43, 2010, No 11, pp. 3853-3865.10.1016/j.patcog.2010.05.019Search in Google Scholar

39. Hassaïne, A., S. Al-Maadeed, A. Bouridane. A Set of Geometrical Features for Writer Identification. – Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 7667 LNCS, 2012, pp. 584-591.10.1007/978-3-642-34500-5_69Search in Google Scholar

40. Jiang, N. Research on Gradient Local Binary Patterns Method for Human Detection. 2013, No February.Search in Google Scholar

41. Dalal, N., B. Triggs, N. Dalal, B. Triggs. Histograms of Oriented Gradients for Human Detection. – IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005, pp. 886-893.Search in Google Scholar

42. Yilmaz, M. B., B. Yanikoglu, C. Tirkaz, A. Kholmatov. Offline Signature Verification Using Classifier Combination of HOG and LBP Features. – In: 2011 International Joint Conference on Biometrics, (IJCB’2011), 2011, No October 2015.10.1109/IJCB.2011.6117473Search in Google Scholar

43. Déniz, O., G. Bueno, J. Salido, F. De Torre. Face Recognition Using Histograms of Oriented Gradients.pdf. Vol. 32, 2011, pp. 1598-1603.10.1016/j.patrec.2011.01.004Search in Google Scholar

44. Bai, L., Y. Li, M. Hui. Face Recognition Based on Wavelet Kernel Non-Negative Matrix Factorization. – Cybernetics and Information Technologies, Vol. 14, 2014, No 3, pp. 37-45.10.2478/cait-2014-0031Search in Google Scholar

45. Lowe, D. G. Distinctive Image Features from Scale-Invariant Keypoints. – International Journal of Computer Vision, Vol. 60, 2004, No 2, pp. 1-28.10.1023/B:VISI.0000029664.99615.94Search in Google Scholar

46. Ulusoy, I., C. Bishop. Comparison of Generative and Discriminative Techniques for Object Detection and Classification. – Toward Category-Level Object Recognition, 2006, pp. 173-195.10.1007/11957959_9Search in Google Scholar

47. Kumar, R., S. K. Srivastava. Machine Learning: A Review on Binary Classification. – International Journal of Computer Applications, Vol. 160, 2017, No 7, pp. 11-15.10.5120/ijca2017913083Search in Google Scholar

48. Strecht, P., L. Cruz, C. Soares, J. Mendes-Moreira, R. Abreu. PER-08: A Comparative Study of Classification and Regression Algorithms for Modelling Students’ Academic Performance. – Portugal, 2015, pp. 392-395.Search in Google Scholar

49. Dong, H., G. Jian. Parameter Selection of a Support Vector Machine, Based on a Chaotic Particle Swarm Optimization Algorithm. – Cybernetics and Information Technologies, Vol. 15, 2015, No 3, pp. 140-149.10.1515/cait-2015-0047Search in Google Scholar

50. Huanrui, H. New Mixed Kernel Functions of SVM Used in Pattern Recognition. – Cybernetics and Information Technologies, Vol. 16, 2016, No 5, pp. 5-14.10.1515/cait-2016-0047Search in Google Scholar

51. Schölkopf, B., K.-K. Sung, C. J. C. Burges, F. Girosi, P. Niyogi, T. Poggio. Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifier. Vol. 45, 1997, No 11, pp. 2758-2765.10.1109/78.650102Search in Google Scholar

52. Imandoust, S. B., M. Bolandraftar. Application of k-Nearest Neighbor (kNN) Approach for Predicting Economic Events: Theoretical Background. – Int. Journal of Engineering Research and Applications, Vol. 3, 2013, No 5, pp. 605-610.Search in Google Scholar

53. Cutler, A. Random Forests for Survival, Regression, and Classification. – Utah State University. Ovronnaz, Switzerland, 2010, pp. 1-129.Search in Google Scholar

54. Kishor, D. R., N. B. Venkateswarlu. Hybridization of Expectation-Maximization and k-Means Algorithms for Better Clustering Performance. – Cybernetics and Information Technologies, Vol. 16, 2016, No 2, pp. 16-34.10.1515/cait-2016-0017Search in Google Scholar

55. Parvez, T. M., S. A. Mahmoud. Arabic Handwriting Recognition Using Structural and Syntactic Pattern Attributes. – Pattern Recognition, Vol. 46, 2013, No 1, pp. 141-154.10.1016/j.patcog.2012.07.012Search in Google Scholar

56. Gupta, B., P. Uttarakhand, I. A. Rawat. Analysis of Various Decision Tree Algorithms for Classification in Data Mining. – International Journal of Computer Applications, Vol. 163, 2017, No 8, pp. 975-987.10.5120/ijca2017913660Search in Google Scholar

57. Hassanat, A. B., M. A. Abbadi, A. A. Alhasanat. Solving the Problem of the k Parameter in the kNN Classifier Using an Ensemble Learning Approach. – International Journal of Computer Science and Information Security (IJCSIS), Vol. 12, 2014, No 8, pp. 33-39.Search in Google Scholar

58. Guo, G., H. Wang, D. Bell, Y. Bi, K. Greer. Using kNN Model for Automatic Text Categorization. – Soft Computing, Vol. 10, 2006, No 5, pp. 423-430.10.1007/s00500-005-0503-ySearch in Google Scholar

59. Patil, A. B., J. Shaikh. OTSU Thresholding Method for Flower Image Segmentation. 2016, pp. 1-6.Search in Google Scholar

60. Al-Ma’adeed, S., D. Elliman, C. A. Higgins. A Data Base for Arabic Handwritten Text Recognition Research. – In: Proc. of International Workshop on Frontiers in Handwriting Recognition, IWFHR, Vol. 1, 2002, No 1, pp. 485-489.Search in Google Scholar