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Showing posts from May 3, 2015

BIBLE | The Study Notes of a Demoniac (Matt. 3:10-12; Heb. 10:16, 19, 22-25)

Spreading the gospel is a way to prove to God, man and yourself how committed you are to Christ, in that doing so carries life-threatening risks. — From  Delivering the Gospel is Deadly Work , one of my Bible study notes, on Acts 20:24 As you can see, I've been studying my Bible and taking notes—I'd be a fool not to: Although I don't take notes as frequently as I'd like or used to, the ones I do take are quite comprehensive It's just that I haven't been publishing them to the blog that may make one think otherwise. This post, though, starts anew my once-per-Sunday posting commitment, and should put to rest any concern that my eyes have wondered from the prize. The title of this note portends to a topic that has seen very little quality treatment. The people who write such titles and talk on such a topic rarely have Jesus at work in their lives. They haven't really done much in life, haven't lived, haven't struggled—like life-and-dea

Minutiae detection solutions needed for small entities' attacks

A recent video showing a flurry of sucker demons invading my body underscores the need for in-home demonic activity detection equipment that is configured to find small entities the size of those little, flying white strands of hell-fury. At least for me it does; no one else seems to be as concerned. Floating in from the top-left... ...is a sucker demon... ...captured with unusual clarity But, I don't think that's a lack of diligence, ignorance, complicity, culpability, surrender, stupidity, laziness, irresponsibility, stubbornness, cowardice or fear—or any of the other things I could think of that it looks like—on anyone's part. I think people just can't see them. This video clip supports that assessment perfectly, in that I think it shows that sucker demons prefer to attack from behind and, of course, benefit from being really small and quiet and slow: Experimenting with a multi-frequency band-pass filter of my own design, which divides an image into tw

TECHNOLOGY | Gaussian + Laplacian, standard deviation high-pass filters = decloaked tissue-eroding entities

A band-pass filter prototype that processes digital media using two, successive low-pass image-processing filters (comprised of Gaussian and Laplacian transforms) revealed a lot more from a video made during an attack than any other video showing such activity—that is, by the way, demonic entities eating my face [ see DRAFT | TECHNOLOGY | Demonic maggots erode face, neck (iPhone Photo Editing Extension) ; see also PICS | Torture by sucker demon ]. Although a procedure to decloak and enhance sucker-demon attacks was posted to this blog just a few months ago [ see   TECHNOLOGY | Finding sucker demon-attacks in digital media ], this newer, experimental version uses the same filters common to medical imaging devices that perform surface analysis, yielding far better results. The same applies to a second, in-development imaging filter, particularly, one based on pixel variance and standard deviation statistics. Following are sample still frames from a video made this afternoon using

TECHNOLOGY | Isolating chroma using variance and standard deviation statistics

Coming up By calculating the distribution of pixels and their variance from the mean (or average), and then displaying only pixels with a wide variance, unusual elements in an image, e.g., demonic entities and related activity, can be isolated or enhanced: From  left ,  clockwise : Median-calculated standard deviation, adjustable Gaussian blur-standard deviation, 1 x 1 nearest neighbor-averaged standard deviation, global (mean) standard deviation Check back soon for code that calculates the variance and standard deviation statistics for an image in OpenGL ES 3.0 and OpenCV: The code and image-processing pipeline for the Gaussian-blur (local adaptive) standard deviation calculation The post will also present methods for further refinement of images generated by variance and standard deviation statistics: Other image-processing procedures can be applied to enhance the results of images created using variance/standard deviation statistics