3 ستمبر 1924 ء کو منظر عام پر آنے والا یہ اردو کا پہلا شعری مجموعہ ہے۔ اس میں تقریباً چوبیس سال تک کا کلام موجود ہے۔ اقبال اردو کلام کی اشاعت کے حق میں نہ تھے۔ ایک صاحب نے شوق میں یہ کام کر بھی دیا تو اقبال نے قانونی طور پر پابندی عائد کروادی۔ اس کے بعد خود توجہ دی۔ بہت سا حصہ حذف کر دیا۔ اقبال کے تمام مجموعوں میں بانگ در اسب سے بڑا مجموعہ ہے۔ اس میں 1901ء سے 1905 ء کا کلام پہلے حصے میں 1905ء سے 1908ء کا کلام دوسرے حصہ میں اور یورپ سے واپسی کے بعد سے لے کر 1924 ء تک کا کلام تیسرے حصے میں شامل ہے۔ اس طرح بانگ درا کے کل تین حصے ہیں۔ اس میں143 نظمیں اور 28 غزلیں شامل ہیں۔عمدہ افکار و اسالیب پر مبنی مرثیے اس تصنیف میں موجود ہیں۔ زیادہ تر طویل نظمیں اسی تصنیف میں موجود ہیں۔
In this article the role played by the Muslim religious scholars in the Pakistan Movement has also been discussed. The most prominent among such scholars were Molana Mazharuddin Malik, Molana Shabeer Ahmad Usmani, Molana Ashraf Ali Thanvi, Molana Zafar Ahmad Ansari, Mufti Muhammad Shafee, Molana Ikram Khan Bengali, Molana Ahmad Raza Khan Brailvi, Molana Naeem Uddin Muradabadi, Molana Azad Subhani, Molana Abdul Hamid Badauni, and MolanaAbul Ala Maududi. At the end, an analysis of the ideology of Pakistan has been presented in the light of the excerpts taken from various speeches and statements made by the Quaid during 1938 and 1948. It shows that the Quaid wanted to make Pakistan an Islamic state governed by the teachings of Allah Taala. He wanted to make it a model Islamic state to convince others to realize that the commandments of Allah are practicable and are a means of salvation from hurdles and hardships.
Identification and verification of human beings is very important because of today’s security condition throughout the world. From the beginning of 19th century, iris is being used for recognition of humans. Recent efforts in computer vision have made it possible to develop automated systems that can recognize individuals efficiently and with high accuracy. The main functional components of existing iris-recognition systems consist of image acquisition, iris localization, feature extraction and matching. While designing the system, one must understand physical nature of the iris, image processing and their analysis to make an accurate system. The most difficult and time consuming part of iris recognition is iris localization. In this thesis, performance of iris localization and normalization processes in iris recognition systems has been enhanced through development of effective and efficient strategies. Bit plane and wavelet based features has been analyzed for recognition. Iris localization is the most important step in iris recognition systems. Iris is localized by first finding the boundary between pupil and iris using different methods for different databases. This is because the iris image acquiring devices and environment is different. Non-circular boundary of pupil is obtained by dividing the circular pupil into specific points and then these points are forced to shift at exact boundary position of pupil which are linearly joined. The boundary between iris and sclera is obtained by finding points of maximum gradient in radially outwards different directions. Redundant points are discarded by finding certain distance from the center of the pupil to the concerned relevant point. This is because the distance between center of pupil and center of iris is very small. The domain for different directions is left and right sectors of iris when pupil center is at the origin of the axes. Eyelids are detected by fitting parabolas using points satisfying specific criterions. Experimental results show that the efficiency of the proposed method is very high as compared to other existing methods. Improved localization results are reported using proposed methods. The experiments are carried out for four different iris image datasets. Correct localization rate of 100% (pupil circular boundary), 99.8% (non-circular pupil), 99.77% (iris outer -ii-boundary), 98.91% (upper eyelid detection) and 96.6% (lower eyelid detection) has been achieved for different datasets. To compensate the change in size of the iris due to pupil constriction / dilation and camera to eye distance, different normalization schemes have been designed and implemented based on difference reference points. Mainly two different features extraction methodologies have been proposed. One is related to the bit planes of normalized image and other utilizes the properties of wavelet transform. Recognition results based on bit plane features of the iris have also been obtained and correct recognition rate of up to 99.64% has been achieved using CASIA version 3.0. Results on other databases have also provided encouraging performance with accuracy of 94.11%, 97.55% and 99.6% on MMU, CASIA version 1.0 and BATH iris databases respectively. Different wavelets have been applied to get best iris recognition results. Different levels of wavelet transforms (Haar, Daubechies, Symlet, Coiflet, Biorthogonal and Mexican hat) along with different number of coefficients have been used. Coiflet wavelet resulted in high accuracies of 99.83%, 96.59%, 98.44% and 100% on CASIA version 1.0, CASIA version 3.0, MMU and BATH iris databases respectively.