Low-level Feature's Set for Text Image Discrimination
نویسندگان
چکیده
This paper introduces a method for the automatic discrimination of digital images based on their semantic content. The proposed system allows to detect if a digital image contains or not a text document. This is realized by a multi-steps procedure based on low-level feature’s set properly derived. Our experiments show that the proposed algorithm is competitive in efficiency with classical techniques, but it has a lower complexity.
منابع مشابه
Automatic Discrimination of Text Images
This paper introduces a method for the automatic discrimination of digital images based on their semantic content. The proposed system allows to detect if a digital image contains or not a text. This is realized by a multi-steps procedure based on low-level features set properly derived. Our experiments show that the proposed algorithm is competitive in efficiency with classical techniques, and...
متن کاملFiltered Text and Direction Discrimination Training Improved Reading Fluency for Both Dyslexic and Normal Readers
Optometry & Vision Development Abstract Background: Over 67% of children in 4th grade are reading below grade level, which means they are twice as likely to drop out of school. Previous research has found that children who are slow readers have reduced contrast sensitivity for detecting the direction of movement, and that improving their movement contrast sensitivity by training with sinusoidal...
متن کاملDocument Image Dewarping Based on Text Line Detection and Surface Modeling (RESEARCH NOTE)
Document images produced by scanner or digital camera, usually suffer from geometric and photometric distortions. Both of them deteriorate the performance of OCR systems. In this paper, we present a novel method to compensate for undesirable geometric distortions aiming to improve OCR results. Our methodology is based on finding text lines by dynamic local connectivity map and then applying a l...
متن کاملDiscriminating Image Senses by Clustering with Multimodal Features
We discuss Image Sense Discrimination (ISD), and apply a method based on spectral clustering, using multimodal features from the image and text of the embedding web page. We evaluate our method on a new data set of annotated web images, retrieved with ambiguous query terms. Experiments investigate different levels of sense granularity, as well as the impact of text and image features, and globa...
متن کاملA new approach to modeling the influence of image features on fixation selection in scenes
Which image characteristics predict where people fixate when memorizing natural images? To answer this question, we introduce a new analysis approach that combines a novel scene-patch analysis with generalized linear mixed models (GLMMs). Our method allows for (1) directly describing the relationship between continuous feature value and fixation probability, and (2) assessing each feature's uni...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2002