Comics is usually classified into broad categories called "genres" according to its contents such as comedy, horror, science fiction, etc. Because a genre expresses a comics story briefly, people read comics which has contents based on their interest, by relying on comics genres. However, giving only one genre to one comic cannot express the detailed difference of the story. In this paper, we propose a system for generating comics story representation as a sub-sequence of genres. Our comics story representation can be applied to a new search engine based on stories or to a recommendation system which analyzes the tastes of the user's favorite comics by finding comics with similar story representation. We use a deep neural network to classify each page into the corresponding genre. Experimental results confirm the advantage of the proposed system.

The popularity of storing, distributing and reading comic books electronically has made the task of comics analysis an interesting research problem. Different work have been carried out aiming at understanding their layout structure and the graphic content. However the results are still far from universally applicable, largely due to the huge variety in expression styles and page arrangement, especially in manga (Japanese comics). In this paper, we propose a comic image analysis approach using eye-tracking data recorded during manga reading sessions. As humans are extremely capable of interpreting the structured drawing content, and show different reading behaviors based on the nature of the content, their eye movements follow distinguishable patterns over text or graphic regions. Therefore, eye gaze data can add rich information to the understanding of the manga content. Experimental results show that the fixations and saccades indeed form consistent patterns among readers, and can be used for manga textual and graphical analysis.

Comics and manga are one of the most important forms of publication and play a major role in spreading culture all over the world. In this paper we focus on balloons and their association to comic characters or more generally text and graphic links retrieval. This information is not directly encoded in the image, whether scanned or digital-born, it has to be understood according to other information present in the image. Such high level information allows new browsing experience and story understanding (e.g. dialog analysis, situation retrieval). We propose a speech balloon and comic character association method able to retrieve which character is emitting which speech balloon. The proposed method is based on geometric graph analysis and anchor point selection. This work has been evaluated over various comic book styles from the eBDtheque dataset and also a volume of the Kingdom manga series.

Template matching is a technique used in classifying an object by comparing portions of images with another image. Finding a given template in an image is typically performed by scanning the image and evaluating the similarity with the template. When the scanning is concerned with the entire image template matching is optimal. This paper considers a special case of template matching where the templates are binary. Although binary template matching has been studied extensively since the early days of pattern recognition, this technique seems not longer in use in Document Image Analysis (DIA). The major reasons arête time complexity, the no-invariance to scale and rotation and the lack of adaptability of similarity measures. However, different contributions have been investigated during the last years to improve these aspects: robustness and discrimination capability of similarity measures, their characterization, time-processing optimization with hardware support, etc. In this paper, we will review first some of the recent issues about binary template matching. We will present then a system exploiting bitwise operators and parallel processing supporting fast and accurate binary template matching for Manga copyright protection. This system is compared to a FFT-based template matching, and it outperforms both in processing-time and detection accuracy.

Manga (Japanese style comics) is one of the most popular publications. Nowadays manga is often handled as digital images not only in consumers' use but also in digital media. However, they hardly handle manga as content-based materials. Some digital media use tags or text data for retrieval, where the tags and text data are produced by handmade input. Therefore our goal is achieving content-based retrieval method for manga images. As the first step to the goal, we investigate the performance of Sun's method applying to manga character retrieval. Manga character retrieval means a image retrieval of which the input and output are a character image and page images where the input character appears respectively. It is useful for convenient use of manga images, for example, character retrieval or auto-tagging. We modify Sun's method so as to be applicable to manga character retrieval and then investigate the performance.

Digital watermarking is a technique that embeds additional data into digital contents so that the distortion by embedding them is imperceptible, where the additional data are called watermark. One of the applications of digital watermarking is tamper detection and recovery. The digital watermarking methods for tamper detection and recovery can detect the tampered region in a tampered image and recover it. In this application, the digital watermarking methods solve the problem that digital contents can be tampered so that the falsification is not detected. In this manuscript, we propose a new method for tamper detection and recovery of JPEG images by using a RS code. The proposed method embeds the check symbols corresponding to an information-reduced original image into the LSBs of the quantized DCT coefficients in a JPEG image directly. Therefore the method completely extracts the embedded data from watermarked JPEG images. We investigated the performance of the proposed method in view of the image quality and the ability of tamper detection and recovery. The experiments of the image quality confirmed the imperceptibility of watermarked images and images used for recovery. The experiments of the ability of tamper detection and recovery confirmed the maximum size of recoverable tampered region and the difficulty of undetectable falsification.

The objective of this work is to embed watermark information into digital audio data as the deterioration of sound quality is not perceivable to human ears. Hence, we consider that watermark information is embedded in the consonance to melody line or bass line. Generally, unison, octave, perfect fifth and perfect fourth are called consonance and human ears can hardly feel annoyed for consonance. Hence, we focus on perfect fifth and perfect fourth in the consonance. For decision of embedding positions, we need to estimate tone pitches, and we use spectrogram analysis as a technique of automatic music transcription. We embed watermark information with perfect fifth or perfect fourth of consonance from the pitch which is estimated by spectrogram analysis, and we aim at good sound quality of watermarked audio signal without sense of discomfort. Therefore, we propose an audio watermarking method by using automatic music transcription information.