In major congenital heart ailments comes Atrial Septal Defect (ASD). Many techniques viz. ECG, MRI, Ultrasound etc., are in use to detect ASD. Performance of heart is analyzed by the Doctors through test results or observations of heart Ultrasound. In this research work it is proved that the disorder ASD is detected using the technique of block matching and optical flow. These algorithms enables the doctors or experts to detect ASD automatically and hence reduces the dependency on humans. This paper proposes a new Elongated Horizontal Large Diamond Search Pattern (EHLDSP) and Optical Flow algorithm for detection of ASD based on MV. Experimentation was carried out on A4C view of 2D Echo Cardiogram, collected form the hospitals as well as from open available database. Ground truth image is used by the cardiologist to compare the results. In this paper, performance of the proposed Elongated Horizontal Large Diamond Search Pattern (EHLDSP) method is compared with other techniques on the basis of cost functions like PSNR and computation complexity. EHLDSP algorithm is used to check the pixel movements and to calculate Motion Vector (MV), followed by the estimation of the displacement of blood cells from either right to left or vice versa. This will help in the reduction of dependency on specialized doctors or human factor can be reduced. For automatic detection of abnormality, research is going on in this area to make it fast and accurate. Proposed algorithm reduces the average computation by providing speed improvements of about 91% over FS/ES and about 6% over existing DS. Also, EHLDSP has shown improvements in the PSNR value in comparison with other methods.