Room 70-3500 (Golisano College)
Department of Computer Science
Rochester Institute of Technology
Phone: (585) 475-4536

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Publications

Publications by Topic

Doctoral Dissertations

K. Davila (2017) Symbolic and Visual Retrieval of Mathematical Notation using Formula Graph Symbol Pair Matching and Structural Alignment. PhD Dissertation. Rochester Institute of Technology (Computing and Information Sciences), NY, USA (July 2017).

L. Hu (2016) Features and Algorithms for Visual Parsing of Handwritten Mathematical Expressions. PhD Dissertation. Rochester Institute of Techology (Computing and Information Sciences), NY, USA (May 2016).

S. Zhu (2016) Text Detection for Natural Scenes and Technical Diagrams with Convolutional Features and Cascaded Classification. PhD Dissertation. Rochester Institute of Technology (Imaging Science), NY, USA (May 2016).

MSc Theses

K. Aziz (2017) Better Text Detection through Improved k-means-based Feature Learning. Master's Thesis. Rochester Institute of Technology (Computer Science), NY, USA (July 2017).

M. Condon (2017) Applying Hierarchical Contextual Parsing with Visual Density and Geometric Features to Typeset Formula Recognition. Master's Thesis. Rochester Institute of Technology (Computer Science), NY, USA (June 2017).

A. Pillay (2014) Intelligent Combination of Structural Analysis Algorithms: Application to Mathematical Expression Recognition. Master's Thesis. Rochester Institute of Technology (Computer Science), NY, USA (June 2014).

K. Del Valle Wangari (2013) Discovering real-world usage scenarios for a multimodal math search interface. Master's Thesis, Rochester Institute of Technology (Human-Computer Interaction), NY, USA (December 2013).

D. Stalnaker (2013) Math Expression Retrieval Using Symbol Pairs in Layout Trees. Master's Thesis, Rochester Institute of Technology (Computer Science), NY, USA (August 2013).

M. Reichenbach (2013) Improving Accuracy of Relevance Assessment for Math Search using Rendered Expressions. Master's thesis, Rochester Institute of Technology (Human-Computer Interaction), NY, USA (May 2013).

T. Schellenberg (2011) Layout-Based Substitution Tree Indexing and Retrieval for Mathematical Expressions. Master's thesis, Rochester Institute of Technology (Computer Science), NY, USA (November 2011).

B. Holm (2011) Evaluation of RSL History as a Tool for Assistance in the Development and Evaluation of Computer Vision Algorithms. Master's thesis, Rochester Institute of Technology (Computer Science), NY, USA (August 2011).

D. Snyder (2011) Text Detection in Natural Scenes through Weighted Majority Voting of DCT High Pass Filters, Line Removal, and Color Consistency Filtering. Master's thesis, Rochester Institute of Technology (Imaging Science), NY, USA (May 2011).

L. Yu (2010) Image-Based Math Retrieval Using Handwritten Queries, Master's thesis, Rochester Institute of Technology (Computer Science), NY, USA (May, 2010).

L. Ouyang. (2009) A Symbol Layout Classification for Mathematical Formulas Using Layout Context, Master's thesis, Rochester Institute of Technology (Imaging Science), NY, USA (Nov. 2009).

K. Kluever. (2008) Evaluating the Usability and Security of a Video CAPTCHA. Master's thesis, Rochester Institute of Technology (Computer Science), NY, USA (Aug. 2008).

MSc and BSc Projects

R. Dashora (2018) Recognition of Mathematical Formulas in PDF Documents. Master's Project. Rochester Institute of Technology (Computer Science), NY, USA (May 2018).

S. Godge (2018) Generating Label Graph Output from a Neural Math Parser. Master's Project. Rochester Institute of Technology (Computer Science), NY, USA (May 2018).

A. Murthy (2018) Character Localization for Text Detection in Natural Scenes. Master's Project. Rochester Institute of Technology (Computer Science), NY, USA (May 2018).

R. Joshi (2017) Extraction of Mathematical Expressions from Scholarly Documents. Master's Project. Rochester Institute of Technology (Computer Science), NY, USA (Dec. 2017).

L. Ravi (2017) Parsing Handwritten Math Formulas. Master's Project. Rochester Institute of Technology (Computer Science), NY, USA (May 2017). (Second place for Best MS Project Poster Award).

C. Jain (2016) Recognition of Online Handwritten Math Symbols using Density Features. Master's Project. Rochester Institute of Technology (Computer Science), NY, USA (Dec. 2016). (Second place for MS Project Best Poster Award) Report is available online here.

K-Y. Choi (2016) Segmentation and Recognition of Symbols for Printed and Handwritten Music Scores. Master's Research Internship Report. INSA, Rennes, France (June 2016; co-advised with B. Coüasnon and Y. Ricquebourg, INSA).

Y. Huang (2016) Web Framework for Evaluating Handwritten Math Recognition. Master's Project. Rochester Institute of Technology (Computer Science), NY, USA (May 2016). Report is available online here.

K. Calangutkar (2015) Classification of Handwritten Math Symbols using Random Forst and Hybrid Features. Master's Project. Rochester Institute of Technology (Computer Science), NY, USA (Dec. 2015). (Second-place for best poster award in CS MS Project Poster Session)

M. Kanadje (2015) Keyword Spotting in Audio to Support Video Lecture Indexing. Master's Project. Rochester Institute of Technology (Computer Science), NY, USA (May 2015).

K. Talmadge (2014) Using the Recognition Strategy Library to Study the Behavior of a Math Recognition System. Master's Project. Rochester Institute of Technology (Computer Science), NY, USA (August 2014). (poster)

Z. Miller (2014) Keyword Spotting in Audio for AccessMath (Best poster award for Spring 2014 RIT Computer Science MS Project Poster Session; co-advisors: R. Gaborski and R. Zanibbi) Master's Project. Rochester Institute of Technology (Computer Science), NY, USA (May 2014).

N. Pattaniyil (2014) Tangent 1.1: Math and Text Search Engine (poster) Master's Project. Rochester Institute of Technology (Computer Science), NY, USA (May 2014). [ NTCIR-11 Conference Poster and slides ]

C. Sasarak (2014) Recognition Strategy Library (RSLib) (poster) Master's Project, Rochester Institute of Technology (Computer Science), NY, USA (May 2014).

A. Canter (2013) Assessing Threat Posted to Video CAPTCHA by OCR-Based Attacks. Master's Project, Rochester Institute of Technology (Computer Science), NY, USA (June 2013).

K. Davila (2013) Math Expression Retrieval Implemented through Sketches. Master's project, Rochester Institute of Technology (Computer Science), NY, USA (May 2013).

G. Chen (2013) Text Inpainting and its Application in Video CAPTCHA Text Removal. Senior Undergraduate Project, Rochester Institute of Technology (Imaging Science), NY, USA (May 2013). [ Poster ]

Text Detection and OCR

Davila, K. and Zanibbi, R. (2017) Whiteboard Video Summarization via Spatio-Temporal Conflict Minimization. Proc. Int'l Conf. Document Analysis and Recognition (ICDAR), Kyoto, Japan (to appear).

S. Zhu and R. Zanibbi (2016). A Text Detection System for Natural Scenes with Convolutional Feature Learning and Cascaded Classification. Proc. Computer Vision and Pattern Recognition (CVPR), pp. 625-632, Las Vegas. Final version available from IEEE Xplore.

C. Riedl, R. Zanibbi, M.A. Hearst, S. Zhu, M. Menietti, J. Crusan, I. Metelsky, K.R. Lakhani (2016) Detecting figures and part labels in patents: competition-based development of graphics recognition algorithms. Int'l J. Document Analysis and Recognition, 19(2): 155-172. (original publication available from www.springerlink.com).

S. Zhu and R. Zanibbi (2013) Label Detection and Recognition for USPTO Images using Convolutional K-means Feature Quantization and AdaBoost. Proc. Int'l Conf. Document Analysis and Recognition, pp. 1428-1432, Washington, DC.

Mathematical Information Retrieval (MIR)

Davila, K. and Zanibbi, R. (2018) Visual Search Engine for Handwritten and Typeset Math in Lecture Videos and LaTeX Notes. Proc. Int'l Conf. Frontiers in Handwriting Recognition, Niagara Falls, NY (Best Paper Award).

Davila, K. and Zanibbi, R. (2017) Layout and Semantics: Combining Representations for Math Formula Search. Proc. ACM Special Interest Group on Information Retrieval (SIGIR), Tokyo, Japan (to appear).

R. Zanibbi, K. Davlia, A. Kane and F. Tompa (2016) Multi-Stage Math Formula Search: Using Appearance-Based Similarity Metrics at Scale. Proc. ACM Special Interest Group on Information Retrieval (SIGIR), pp. 145-154, Pisa, Italy.

K. Davila. (2016) Appearance-Based Retrieval of Mathematical Notation in Documents and Lecture Videos. Proc. ACM Special Interest Group on Information Retrieval (SIGIR), (abstract), pp. 1165-1165, Pisa, Italy.

R. Zanibbi, A. Aizawa, M. Kohlhase, I. Ounis, G. Topic and K. Davila. (2016) NTCIR-12 MathIR Task Overview. Proc. NTCIR-12, Tokyo (online proceedings).

K. Davila, R. Zanibbi, A. Kane and F.W. Tompa (2016) Tangent-3 at the NTCIR-12 MathIR Task. Proc. NTCIR-12, Tokyo (online proceedings).

M. Kanadje, Z. Miller, A. Agarwal, R. Gaborski, R. Zanibbi and S. Ludi. (2016) Assisted keyword indexing for lecture videos using unsupervised keyword spotting. Pattern Recognition Letters, 71(1):8--15. (Online demonstration). Final version available online from Elsevier.

H. Chatbri, K. Davila, K. Kameyama and R. Zanibbi (2015) Shape matching using keypoints extracted from both the foreground and the background of binary images. Proc. Int'l Conf. Image Processing Theory, Tools and Applications, pp. 205-210, Orleans, France.

Zanibbi, R. and Orakwue, A. (2015) Math Search for the Masses: Multimodal Search Interfaces and Appearance-Based Retrieval. Proc. Conference on Intelligent Computer Mathematics (CICM), LNAI 9150, Springer, pp. 18-36, Washington, DC.

Stalnaker, D. and Zanibbi, R. (2015) Math expression retrieval using an inverted index over symbol pairs. Proc. SPIE Document Recognition and Retrieval, Vol. 9402, pp. 07(1)-07(12), San Francisco.

Pattaniyil, N. and Zanibbi, R. (2014) Combining TF-IDF Text Retrieval with an Inverted Index over Symbol Pairs in Math Expressions: The Tangent Math Search Engine at NTCIR 2014. Proc. 11th NII Testbeds and Community for Information access Research (NTCIR), Tokyo, Japan (online, 8pp.).

Reichenbach, M.S., Agarwal, A. and Zanibbi, R. (2014) Rendering expressions to improve accuracy of relevance assessment for math search. Proc. ACM SIGIR, Gold Coast, Australia, pp. 851-854.

Del Valle Wangari, K., Zanibbi, R. and Agarwal, A. (2014) Discovering real-world use cases for a multimodal math search interface. Proc. ACM SIGIR, Gold Coast, Australia, pp. 947-950.

Davila, K.M., Agarwal, A., Gaborski, R., Zanibbi, R., and Ludi, S. (2013) AccessMath: Indexing and retrieving video segments containing math expressions based on visual similarity. Proc. IEEE Western New York Image Processing Conference, Rochester, NY (online, 4pp.)

S. Zhu, L. Hu and R. Zanibbi (2013) Rotation-Robust Math Symbol Recognition and Retrieval Using Outer Contours and Image Subsampling Proc. Document Recognition and Retrieval, SPIE vol. 8658, pp. OI:1-8, San Francisco, CA.

R. Zanibbi and D. Blostein (2012) Recognition and Retrieval of Mathematical Expressions, Int'l. Journal on Document Analysis and Recognition 15(4): 331-357. (original publication available from www.springerlink.com).

C. Sasarak, K. Hart, R. Pospesel, D. Stalnaker, L. Hu, R. LiVolsi, S. Zhu, and R. Zanibbi. (2012) min: A Multimodal Web Interface for Math Search. Symp. Human-Computer Interaction and Information Retrieval, Cambridge, MA (online, 4pp).

T. Schellenberg, B. Yuan and R. Zanibbi (2012). Layout-based substitution tree indexing and retrieval for mathematical expressions, Proc. Document Recognition and Retrieval XIX, pp. 8297OI-1 - 8297OI-8, San Francisco.

R. Zanibbi and L. Yu. (2011) Math Spotting: Retrieving Math in Technical Documents Using Handwritten Query Images. Proc. Int'l Conf. Document Analysis and Recognition, pp. 446-451, Beijing.

R. Zanibbi and B. Yuan. (2011) Keyword and image-based retrieval of mathematical expressions. Proc. Document Recognition and Retrieval XVIII, vol. 7874 Proc. SPIE, pp. OI1-OI9, San Francisco, CA.

L. Yu and R. Zanibbi. (2009) Math Spotting in Technical Documents Using Handwritten Queries, Int'l Workshop on Pen-Based Mathematical Computation (extended abstract).

Math Recognition

M. Mahdavi, M. Condon, and R. Zanibbi (2018) Applying Hierarchical Contextual Parsing to Isolated Typeset Math Formulas. Western New York Image Processing Workshop (WNYIP), Rochester, NY, USA. (poster)

L. Hu and R. Zanibbi. (2016) MST-Based Visual Parsing of Online Handwritten Mathematical Expressions. Proc. Int'l Conf. Frontiers in Handwriting Recognition, Shenzhen, China (to appear).

L. Hu and R. Zanibbi. (2016) Line-of-Sight Stroke Graphs and Parzen Shape Context Features for Handwritten Math Formula Representation and Symbol Segmentation. Proc. Int'l Conf. Frontiers in Handwriting Recognition, Shenzhen, China (to appear).

H Mouchere, C. Viard-Gaudin, R. Zanibbi and U. Garain. (2016) ICFHR 2016 CROHME: Competition on Recognition of Online Handwritten Mathematical Expressions.. Proc. Int'l Conf. Frontiers in Handwriting Recognition, Shenzhen, China (to appear).

H. Mouchere, R. Zanibbi, U. Garain and C. Viard-Gaudin. (2016) Advancing the State-of-the-Art for Handwritten Math Recognition: The CROHME Competitions, 2011-2014. Int'l Journal on Document Analysis and Recognition, 19(2): 173-189. (original publication available from www.springerlink.com).

Davila, K.M., Ludi, S. and Zanibbi, R. (2014) Using off-line features and synthetic data for on-line handwritten math symbol recognition. Proc. Int'l Conf. Frontiers in Handwriting Recognition, pp. 323-328, Crete, Greece.

Mouchere, H., Viard-Gaudin, C., Zanibbi, R. and Garain, U. (2014) ICFHR 2014 Competition on Recognition of On-line Handwritten Mathematical Expressions (CROHME 2014). Proc. Int'l Conf. Frontiers in Handwriting Recognition, pp. 791-796, Crete, Greece.

D. Blostein and R. Zanibbi. (2014) Processing Mathematical Notation, Chapter 5.6 in Handbook of Document Image Processing and Recognition, pp. 679-702, Springer-Verlag.

F. Alvaro and R. Zanibbi (2013) A Shape-Based Layout Descriptor for Classifying Spatial Relationships in Handwritten Math. ACM Symp. Document Engineering, Florence, Italy, pp. 123-126.

L. Hu and R. Zanibbi (2013) Segmenting Handwritten Math Symbols Using AdaBoost and Multi-Scale Shape Context Features. Proc. Int'l Conf. Document Analysis and Recognition, pp. 1180-1184, Washington, DC.

S. Zhu, L. Hu and R. Zanibbi (2013) Rotation-Robust Math Symbol Recognition and Retrieval Using Outer Contours and Image Subsampling Proc. Document Recognition and Retrieval, Proc. SPIE vol. 8658, pp. 05-1 - 05-12, San Francisco, CA.

R. Zanibbi and D. Blostein (2012) Recognition and Retrieval of Mathematical Expressions, Int'l. Journal on Document Analysis and Recognition 15(4): 331-357. (original publication available from www.springerlink.com).

L. Hu, K. Hart, R. Pospesel, and R. Zanibbi. (2012) Baseline extraction-driven parsing of handwritten mathematical expressions Proc. Int'l Conf. Pattern Recognition, Tsukuba Science City, Japan.

L. Hu and R. Zanibbi. (2011) HMM-Based Recognition of Online Handwritten Mathematical Symbols Using Segmental K-means Initialization and a Modified Pen-up/down Feature. Proc. Int'l. Conf. Document Analysis and Recognition, pp. 457-462, Beijing.

L. Ouyang and R. Zanibbi. (2009) Identifying Layout Classes for Mathematical Symbols using Layout Context, Proc. IEEE Western New York Image Processing Workshop (extended abstract).

L. Ouyang and R. Zanibbi. (2009) Handwritten Mathematical Symbol Classification Using Layout Context, Int'l Workshop on Pen-Based Mathematical Computation (extended abstract).

A. Pillay and R. Zanibbi. (2009) Intelligent Combination of Structural Analysis Algorithms: Application to Mathematical Expression Recognition, Int'l Workshop on Pen-Based Mathematical Computation (extended abstract).

L. Zhang, D. Blostein, and R. Zanibbi. (2005) Using Fuzzy Logic to Analyze Superscript and Subscript Relations in Handwritten Mathematical Expressions, in Proc. Int'l Conf. Document Analysis and Recognition, pp. 972-976, Seoul, Korea.

R. Zanibbi, D. Blostein, and J.R. Cordy. (2002) Recognizing Mathematical Expressions Using Tree Transformation, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 24, No. 11, pp. 1455-1467. (The original publication is available at ieeexplore.ieee.org)

D. Blostein, J.R. Cordy and R. Zanibbi. (2002) Applying Compiler Techniques to Diagram Recognition, in Proc. Sixteenth Int'l Conference on Pattern Recognition, Vol. 3, pp. 123-126, Quebec City, Canada.

D. Blostein, E. Lank, A. Rose, and R. Zanibbi. (2002) User Interfaces for On-Line Diagram Recognition, in Graphics Recognition: Algorithms and Applications, Lecture Notes in Computer Science, Vol. 2390, pp. 92-103.

R. Zanibbi, K. Novins, J. Arvo and K. Zanibbi. (2001) Aiding Manipulation of Handwritten Mathematical Expressions through Style-Preserving Morphs, In Proc. Graphics Interface 2001, Ottawa, Canada, pp. 127-134.

Music Notation Recognition

Choi, K.-Y., Couasnon, B., Ricquebourg, Y., and Zanibbi, R. (2018) Music symbol detection with Faster R-CNN using synthetic annotations. Proc. Int'l Work. Reading Music Systems, Paris, France, pp. 9-10. (abstract)

B. Coüasnon, A. Popat and R. Zanibbi. Discussion Group Summary: Graphics Syntax in the Deep Learning Age. Proc. Work. Graphics Recognition 2017, 4 pp., to appear, 2018.

K.-Y. Choi, B. Coüasnon, Yann Ricquebourg and R. Zanibbi. Music Symbol Detection with Faster R-CNN Using Synthetic Annotations. Proc. Int'l Work. Reading Music Systems (WoRMS), 2 pp., to appear (abstract), 2018.

Pacha, A., Choi, K-Y., Couasnon, B., Ricquebourg, Y., Zanibbi, R. and Eidenberger, H. (2018) Handwritten Music Object Detection: Open Issues and Baseline Results. Proc. IAPR W. on Document Analysis Systems (DAS), Vienna, Austria (to appear).

Choi, K.Y., Couasnon, B., Ricquebourg, Y. and Zanibbi, R. (2017) Bootstrapping Samples of Accidentals in Dense Piano Scores for CNN-Based Detection. Proc. IAPR Int'l. W. on Graphics Recognition (GREC), Kyoto, Japan (abstract; to appear)

Video CAPTCHAs

K. Kluever and R. Zanibbi. (2009) Balancing Usability and Security in a Video CAPTCHA, in Proc. Symposium on Usable Privacy and Security (archived online in the ACM International Conference Proceeding Series).

K. Kluever and R. Zanibbi. (2008) Video CAPTCHAs: Usability vs. Security. Proc. IEEE Western New York Image Processing Workshop, Rochester, NY (USA) (extended abstract).

K. Kluever. (2008) Breaking the PayPal HIP: A Comparison of Classifiers. (RIT Department of Computer Science Technical Report).

Evaluating Pattern Recognition Systems

R. Zanibbi, H. Mouchere, and C. Viard-Gaudin (2013) Evaluating Structural Pattern Recognition for Handwritten Math via Primitive Label Graphs Proc. Document Recognition and Retrieval, Proc. SPIE vol. 8658, pp. 17-1 - 17-11, San Francisco, CA.

R. Zanibbi, A. Pillay, H. Mouchere, C. Viard-Gaudin, and D. Blostein. (2011) Stroke-Based Performance Metrics for Handwritten Mathematical Expressions. Int'l Conf. Document Analysis and Recognition, pp. 334-338, Beijing.

R. Zanibbi, D. Blostein, and J.R. Cordy. (2009) White-Box Evaluation of Computer Vision Algorithms through Explicit Decision-Making, Proc. Int'l. Conf. Computer Vision Systems, Lecture Notes in Computer Science, Vol. 5815, pp. 295-304.

R. Zanibbi, D. Blostein, and J.R. Cordy. (2008) Decision-Based Specification and Comparison of Table Recognition Algorithms, in Machine Learning in Document Analysis and Recognition, Springer Studies in Computational Intelligence, Vol. 90, pp. 71-103 (original version is available from www.springerlink.com).

R. Zanibbi, D. Blostein, and J.R. Cordy. (2006) Decision-Based Specification and Comparison of Table Recognition Strategies. Proc. IEEE Western New York Image Processing Workshop, Rochester, NY (USA) (extended abstract)

R. Zanibbi, D. Blostein, and J.R. Cordy. (2005) The Recognition Strategy Language, in Proc. Int'l Conf. Document Analysis and Recognition, pp. 565-569, Seoul, Korea.

R. Zanibbi, D. Blostein, and J.R. Cordy. (2005) Historical Recall and Precision: Summarizing Generated Hypotheses, in Proc. Int'l Conf. Document Analysis and Recognition, pp. 202-206, Seoul, Korea.

R. Zanibbi, D. Blostein, and J.R. Cordy. (2005) Recognition Tasks are Imitation Games, in Pattern Recognition and Data Mining, Eds. S. Singh et al., Lecture Notes in Computer Science, Vol. 3686, pp. 209-218.

Miscellaneous Document Recognition

C. Bigelow and R. Zanibbi (2015) Analysis Of Typographical Trends In European Printing 1470-1660. Proc. Conf. of the American Printing History Association.

C. Riedel, R. Zanibbi, M.A. Hearst, S. Zhu, M. Menietti, J. Crusan, I. Metelsky, and K.R. Lakhani. (Oct. 2014) Detecting Figures and Part Labels in Patents: Competition-Based Development of Image Processing Algorithms. Harvard-NASA Tournament Lab Technical Report 01 (Harvard University, Cambridge, MA).

R. LiVolsi, R. Zanibbi, and C. Bigelow. (2012) Collecting historical font metrics from Google Books. Proc. Int'l Conf. Pattern Recognition, Tsukuba Science City, Japan.

J.C. Handley, A.M. Namboodiri, and R. Zanibbi. (2005) Document Understanding System Using Stochastic Context-Free Grammars, in Proc. Int'l Conf. Document Analysis and Recognition, pp. 511-515, Seoul, Korea.

R. Zanibbi, D. Blostein, and J.R. Cordy. (2004) A Survey of Table Recognition: Models, Observations, Transformations, and Inferences, Int'l J. Document Analysis and Recognition, Vol. 7, No. 1, pp. 1-16. (The original publication is available at www.springerlink.com)

D. Blostein, R. Zanibbi, G. Nagy, R. Harrap. (2003) Document Representations. Proc. Fifth IAPR Int'l Workshop on Graphics Recognition (GREC 2003), Barcelona, Spain, pp. 3-12.