Affective Relationship between Color and Text in Arabic Comic Books

Comic books are considered a heritage in many countries. The colorful depiction of annotated events has gained an increasing amount of interest over the past decade as the digitization process took over printed media, in addition to the abundance and variety of available data. Several applications have been devised in the field of computer vision and natural language processing to handle comic book pages. However, in this paper, we focus on the connection between the two, specifically, we compare the emotions that color and text separately imply. The theory of color and its effect on one's emotional state can be dated back to the 1800's. The language used in speech balloons is also written to a way to capture the audience's attention and manipulate their emotions. Throughout this paper, the color theory is applied to analyze the pages' emotional implication, and compared to the output of minSVM, a modified SVM classifier that accommodates imbalanced datasets, and a regular SVM, that are trained and implemented on the extracted text of a homegrown database to identify the emotions they convey. Using minSVM, we obtained a 91.26 % accuracy as opposed to an 89.66 % with SVM.

[1]  Lianhong Cai,et al.  Interpretable aesthetic features for affective image classification , 2013, 2013 IEEE International Conference on Image Processing.

[2]  James Ze Wang,et al.  On shape and the computability of emotions , 2012, ACM Multimedia.

[3]  Eunjung Han,et al.  Frame Segmentation Used MLP-Based X-Y Recursive for Mobile Cartoon Content , 2007, HCI.

[4]  Kenji Shoji,et al.  Layout Analysis of Tree-Structured Scene Frames in Comic Images , 2007, IJCAI.

[5]  Jean-Christophe Burie,et al.  Adaptive Contour Classification of Comics Speech Balloons , 2013, GREC.

[6]  Joost van de Weijer,et al.  An Active Contour Model for Speech Balloon Detection in Comics , 2013, 2013 12th International Conference on Document Analysis and Recognition.

[7]  Laila Khreisat,et al.  Arabic Text Classification Using N-Gram Frequency Statistics A Comparative Study , 2006, DMIN.

[8]  Daniel Cohen-Or,et al.  Optimizing Photo Composition , 2010, Comput. Graph. Forum.

[9]  Martin Stommel,et al.  Segmentation-Free Detection of Comic Panels , 2012, ICCVG.

[10]  Taku Komura,et al.  Automatic Panel Extraction of Color Comic Images , 2007, PCM.

[11]  Jean-Christophe Burie,et al.  Panel and Speech Balloon Extraction from Comic Books , 2012, 2012 10th IAPR International Workshop on Document Analysis Systems.

[12]  Alaa M. El-Halees,et al.  Arabic Text Classification Using Maximum Entropy , 2015 .

[13]  Christophe Ponsard,et al.  An Accessible Viewer for Digital Comic Books , 2008, ICCHP.

[14]  Allan Hanbury,et al.  Affective image classification using features inspired by psychology and art theory , 2010, ACM Multimedia.

[15]  N. A. Nijdam Mapping emotion to color , 2005 .

[16]  Xin Guo Ming,et al.  A Color Harmony Measure Model with Shape Information , 2009, 2009 International Joint Conference on Computational Sciences and Optimization.

[17]  Zhi Tang,et al.  An R-CNN Based Method to Localize Speech Balloons in Comics , 2016, MMM.

[18]  Jean-Christophe Burie,et al.  Robust Frame and Text Extraction from Comic Books , 2011, GREC.

[19]  Abdulmohsen Al-Thubaity,et al.  Automatic Arabic Text Classification , 2008 .

[20]  Ryosuke Yamanishi,et al.  Relation Analysis between Speech Balloon Shapes and their Serif Descriptions in Comic , 2015, 2015 IIAI 4th International Congress on Advanced Applied Informatics.

[21]  Caren Zgheib,et al.  A Musical Classification and Interpretation of Abstract Art , 2013, MindTrek.

[22]  Tarek F. Gharib,et al.  Arabic Text Classification Using Support Vector Machines , 2009, Int. J. Comput. Their Appl..

[23]  Joost van de Weijer,et al.  Automatic Text Localisation in Scanned Comic Books , 2013, VISAPP.

[24]  Eunjung Han,et al.  Automatic Conversion System for Mobile Cartoon Contents , 2005, ICADL.

[25]  Mariette Awad,et al.  Minority SVM for linearly separable imbalanced datasets , 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

[26]  Lianhong Cai,et al.  Affective image adjustment with a single word , 2013, The Visual Computer.