Abstract
Recently, several applications that use image processing technology for object detection have been developed in smart phones. As a main part of image processing technology, image segmentation refers to the process of partitioning a digital image into multiple segments. There are many different image segmentation algorithms that show the good performance on desktop platforms. In this paper, we propose a new seed-based region-growing segmentation algorithm supported by a line-based data structure that allows decreasing the storage space and computation time during the segmentation process and eliminating the drawbacks of the previous algorithms. To deal with uncertainty in region boundaries of real world images, the results of region growing and edge extraction are integrated by a combination of automatic threshold selection for color difference evaluation and edge grow-erode operations that provide more accurate image segmentation. Taking advantage of image processing technologies offered by current cellular phones, this paper presents a new mobile application for measuring building walls for restoration. The implementation and experimental results of the building area measuring application demonstrate the efficiency of the proposed algorithm.
