اپنی تصویر بھی یوں مجھ سے چھپاتی کیوں ہو
دوسرا چہرہ بہانے سے دکھاتی کیوں ہو
تم کو معلوم ہے بنجارے کہیں ٹھہرے ہیں؟
جانے والوں کو بھلا ایسے بلاتی کیوں ہو
ایک شاعر کا یہ شکوہ ہے شکایت بھی ہے
جب دکھانی نہیں تصویر بناتی کیوں ہو
تم بھی مشتاقِ محبت ہو سبھی جانتے ہیں
جذبۂ دل کو بتائو تو چھپاتی کیوں ہو
جب ترے بس میں نہیں روگ محبت والا
تم فضاؔ دل کو یہی روگ لگاتی کیوں ہو
The unique feature of Islam is its comprehensive code of life. This proves its indispensability and worth as the universal order which accommodates complex issues of human life without compromising on its fundamentals. Hence, it is a matchless way of life on this planet. Keeping in view the modern specification of the current age in respect of those countries which tend to modify their legislations and their political, economic and social institutions as per Islamic framework. In this regard, a part from the fundamental and core Islamic sources of jurisprudence like the holy Quran, traditions of the holy Prophet (Hadith), consensus of Muslim scholars (Ijma) and Analogy (Qias), there are other sources like ‘Decorum’ (Istihsan) and ‘Arbitrariness’ (Masalih e Mursalah) to play their effective and significant jurisprudential role to address the numerous social issues by honoring the customs and norms already prevailing in any particular society. The article under discussion speaks of the distinct characteristic of Islam that it is a religion of nature and takes care of natural necessities of human life. Already prevailing customs and norms in human society are not subject to disregard or straight rejection. Islam puts a considerable endeavor not to confront the wisdom of the society by sweeping its norms and customs unnecessarily. Conditions imposed by Islam to formulate any society are specious enough which accommodate many of the customs and encompass overwhelming norms in it. But being the sincere guardian of the humanity, on the other hand, it does not miss its significant reformative role to play with reference to those customs and norms which appear contrary to its fundamentals
Latentfingerprintsaretheimpressionsofpartialridgesleftonthesurfaceofobjects touched unintentionally at crime scenes and constitute a valuable source of evidence in law enforcement agencies to helpsolve crimes. However,majority of the processing (marking regionof interest(ROI),singularpoints(SP),orientationfieldandminutiaepoints)for latentprintsidentificationisdonemanuallybyforensicexperts.Theexistingmethods involve forensicexpertstomanually markthe featuresin latentandtheninput ittothe systemforautomaticmatchingwithreferenceprints.Thematcherreturnsalistof candidates thatare manuallycheckedbyexperts totake final decision.Thepracticeof manuallymarkingfeaturesinlatentsislaborious,timeconsumingandhumandependent whichmayresultsinwrongidentification.Thereforethereisaneedtoautomatethis process to avoid aforesaidconstraints. This thesis describes an automatedapproach of segmentation andenhancement for latent fingerprints identification.Currently,afew attemptshavebeenmade inthisrespectand still remain a challenging problem due to: (i) poor quality, (ii) small friction ridge area,(iii) presence of non-linear distortion,(iv) blurringor smudging,and(v) complexbackground noise. In this research, an algorithm for automated segmentation of latent fingerprints is proposed. The latent image datais classifiedintoclusters using K-means clustering techniquewhich results in pixels having similar characteristicsto fit in one cluster (foreground) while pixels having opposite characteristicsto other cluster (background).Tophat filtering is appliedto enhance the clustered data and mask is generated on the basis of this enhanced information. Segmentation is achievedby applying thegenerated maskon latent image.The proposed algorithm forsegmentationof latent fingerprintsisautomatedwithout anysortof human involvement.Performanceofproposedalgorithmisevaluatedbycomputingthemissed detection rate (MDR) and false detection rate (FDR) and comparison of proposed method withotherexistingalgorithmsisdone.SimulationresultsonNISTSD-27(databaseof latentfingerprintimagescontaining258latentfingerprintsalongwiththeirmatedrolled prints)showsignificantperformanceenhancementofproposedmethodhavingaverage MDR and FDR of 4.77% and 26.06% respectively. Furthermore, subjective comparison is made usingvisual segmentation reliability(VSR)which istheratioof intersectional area ofautomated and ground truthlatent to manually marked segmented latent. VSR approaches to 90% for good quality images, 70-80% for bad quality images and 50-60% for ugly qualityimages.Matchingperformance isimprovedwhen thesegmentedinputis applied to commercial-off-the-shelf(COTS tenprint)matcherascompared with un- segmentedinput. Another contribution of proposed research is towards the enhancement of latent fingerprints. Enhancement of segmented latent isperformed using Gabor filter bank. It has five image-dependent-parameterslikeorientation ∅ ,standarddeviations ?�and ?�ofthe Gaussian function,timeperiodTandthe convolutionmasksize.Theselectionof these parametersplaysacrucial roleinfingerprintenhancementspecificallytheorientation∅ andstandarddeviation ?� and ?� .Thelatentimageis dividedintoblocks of WxW centered at pixel (i,j)and gradients ��� and ��� along x-axis andy-axis are computedby applying Sobel operator at everypixel.Orientation ∅ is computedon the basis ofthese computed gradients. Ridge frequency F(i, j) is estimated by calculating the grey level value of each pixel, housed in the block, and is projected in a direction perpendicular to the local ridgeorientationandridgespacingS(i,j).Animprovementinfrequencyestimationis achievedbyintroducingGaussianlowpassfilterthatminimizesthenoiselevels.Ridge orientation ∅ and frequency F(i, j) is used to design an even-symmetric Gabor filter. Spatial convolution of thelatentfingerprint withGaborfilter isperformedtogenerateenhanced latentimage.SimulationresultsonNISTSD-27showthatimprovementinmatchingis increased 11% in comparison toautomatedlatent fingerprint segmentation and enhancementalgorithmby Zhang et al in 2013.