the architectural education along the way of creativity has often involved with the formal and physical aspects of design as an effort to read architectural artifacts through its mere external appearances. this article, however, aims to step beyond the manifestation of conventional perspectives on visual aspects of built environment. that is, an act of interpreting the architectural spaces thro...

a 2-dimensional visual code marker carries as much as 83 bits information. Thus it is a useful code marker system for storing and extracting information. This paper presents a digital image processing algorithm which automatically locates the marker on a cell-phone camera captured image. With the exact location of the code marker, detailed bits information of the visual code marker is returned....

This report presents our results for the class project for EE368 Digital Image Processing at Stanford University in the Spring of 2006. In this project we detect and decode visual markers by first processing the image to emphasize some salient features, then identify the marker candidates by analyzing these features, and finally projecting each candidate marker to decode it and create error mea...

HE purpose of this project is to detect and read visual code markers in color images taken by camera phones. We are given a set of twelve training images, each containing up to three code markers with arbitrary location and orientation. Each code marker is an 11 x 11 array of black and white elements, 83 of which represent variable data bits. The remaining 38 elements are fixed and consist of t...

This paper describes a proposed solution for the visual code marker detection problem which is one example of object detection applications in digital image processing. The proposed approach is based on performing first image segmentation using adaptive local thresholding. Then regions of potential corners are derived using the region counting algorithm and the spatial characteristics of a corn...

This report describes an algorithm designed to detect visual code markers as described in [1]. The algorithm assumes the images have resolution and quality similar to the ones captured by regular cellular phone cameras. Applications of the use of these visual code markers are described in [2].

An image processing algorithm to detect visual code markers and extract the embedded data is presented. The algorithm uses an adaptive thresholding technique to produce a binary image with an accurate representation of each visual code marker from an input RGB image. Visual code marker detection is performed on the binary image using a series of tests that leverage prior knowledge of the distin...