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A morphological printed English character recognition approaches for binary images is shown in this research. Three morphological operations are used for printed English character recognition: Dilation ,Erosion and Hit-or-Miss.

Morphological filtering is a useful technique for processing and analyzing binary and grayscale images. These filters are effective in impulsive noise filtering, feature extracting, and images enhancing. So it is important to find out method for applying morphological technique on color image and keep the colors unchanged at the same time. This paper deals with the use of morphological filters for suppression "salt & pepper" noise in color images. We have used "component-wise approach", in which grayscale morphological operations are applied to each of the three colors image components independently. We present experimental results of applying this approach for the application of noise suppression in color images.

Detecting circles is very important in the application of image processing especially in determining the object locations. In this paper, a new algorithm is proposed for circle detection, called Point Search Circle Detection (PSCD), which detects points and assumes them as inspection points on the circle circumference by using them to create a virtual circle to match it with the original image. Using matching operation leads to reduce computational operations and reduce the complexity and the running time of the algorithm. The proposed algorithm is highly accurate, has high speed and low storage requirements in comparing with other related algorithms. The proposed algorithm can precisely detect circles with various scales, crossed and nested circles in the binary images. The proposed algorithm was compared with Hough Transform (HT) method for circle detection by using many images with different numbers and radius of circles and different image dimensions. The proposed algorithm was more efficient, where the average ratio of the running time for the proposed algorithm to HT method was 1:646, and the accuracy of the proposed algorithm was 100% for circles detection. Both the proposed and HT algorithms are applied by using Matlab 7.2 language, PC equipment with 1.8MHz Pentium IV processor and 512MB RAM.

In this work a new data hiding algorithm for binary images is used. In this algorithm the pixels which can be flipped without introducing noticeable artifacts are identified at first by using some rules that examine the neighbors of the central pixels in each non-uniform block and then this central pixel only is changed in the block which matches these rules and this property allows easy detection of the embedded data without referring to the original image. Experiments show different results for different binary images. The program is written in MATLAB (6.5).