Text Extraction of Colour Images using Mathematical Morphology & HAAR Transform

Digital image processing is an ever expanding and dynamic area with applications reaching out into our daily life such as digital signature, authentication, surveillance, medicine, space exploration, automated industry inspection and many others areas. Theseapplications are involved in different processes like image enhancement, object detection, features extraction, colour imaging etc. Implementation of such applications on a general purpose computer can be easier, but every time it is not efficient due to additional constraints on memory and other peripheral devices. Out of the five senses – sight, hearing, touch, smell and taste, humans use to perceive their environment. Among all,sight of images is the most powerful. More than 99% of the activity of the human brain is involved in processing images from the visual cortex. A visual image is rich in information. There is an efficient yet simple method to extract text regions from video sequences or static images. The speed of Haar discrete wavelet transform (DWT) operates the fastest among all wavelets because its coefficients are either 1 or -1. It is one of the reasons that Haar DWT is used to detect edges of candidate text regions. Image sub bands contain both text edges and non-text edges. The intensity of the text edges is also different from that of the non-text edges. Therefore, thresholdingis used to preliminary remove the non-text edges. Text regions of colour images are composed of horizontal edges, vertical edges and diagonal edges. Morphological dilation operators as AND, OR are applied to connect isolated text edges of each detail component sub-band in a transformed binary image. The simulation is carried out on MATLAB 2012 image processing tool.