{"id":455,"date":"2025-11-04T10:54:49","date_gmt":"2025-11-04T09:54:49","guid":{"rendered":"https:\/\/ics.science.upjs.sk\/ano\/?page_id=455"},"modified":"2025-11-06T21:10:28","modified_gmt":"2025-11-06T20:10:28","slug":"domace-zadania-2025-s-navodom","status":"publish","type":"page","link":"https:\/\/ics.science.upjs.sk\/ano\/domace-zadania-2025-s-navodom\/","title":{"rendered":"Dom\u00e1ce zadania 2025 s n\u00e1vodom"},"content":{"rendered":"

Vyberte si dve \u00falohy – za ich vyrie\u0161enie m\u00e1te o stupe\u0148 lep\u0161iu zn\u00e1mku (za predpokladu \u00faspe\u0161n\u00e9ho zvl\u00e1dnutia sk\u00fa\u0161ky).<\/em><\/p>\n

A1: Vanishing point (LINK na github classroom<\/a>)<\/strong><\/h2>\n

Implementujte algoritmus pop\u00edsan\u00fd v \u010dl\u00e1nku (Ebrahimpour, R., Rasoolinezhad, R., Hajiabolhasani, Z. and Ebrahimi, M., 2012. Vanishing point detection in corridors: using Hough transform and K-means clustering. IET computer vision, 6(1), pp.40-51.<\/em>).<\/p>\n

\u010cl\u00e1nok na stiahnutie:\u00a0tu<\/a>\u00a0alebo\u00a0tu<\/a>\u00a0(ak by bol probl\u00e9m so stiahnut\u00edm, nap\u00ed\u0161te mi, prepo\u0161lem pdf).<\/p>\n

Konkr\u00e9tne kroky:<\/p>\n

    \n
  1. N\u00e1jdite si obr\u00e1zok chodby. M\u00f4\u017eete prisp\u00f4sobi\u0165 rozl\u00ed\u0161enie. M\u00f4\u017eete pou\u017ei\u0165 aj vlastn\u00fa fotku nejakej chodby. Posta\u010duje jeden obr\u00e1zok, ide\u00e1lne vysk\u00fa\u0161a\u0165 aspo\u0148 na 2-3 obr\u00e1zkoch.<\/li>\n
  2. Obr\u00e1zok konvertujte na \u0161edot\u00f3nov\u00fd<\/li>\n
  3. Ekvalizujte histogram<\/li>\n
  4. Aplikujte 45\u00b0 masku (je v \u010dl\u00e1nku \u2013 ide o maticu 3\u00d73 kde na diagon\u00e1le s\u00fa 2 a na ostatn\u00fdch miestach -1), [[-1,-1,2],[-1,2,-1],[2,-1,-1]]<\/li>\n
  5. Aplikujte Cannyho detektor na detekciu hr\u00e1n<\/li>\n
  6. Pou\u017eite Hough transform\u00e1ciu na z\u00edskanie \u010diar. Odpor\u00fa\u010dam\u00a0HoughLinesP<\/a>, kde je v\u00fdstupom zoznam \u010diar, ktor\u00e9 s\u00fa tvoren\u00e9 \u0161tvoricou \u010d\u00edsel (x a y s\u00faradnice za\u010diato\u010dn\u00e9ho a koncov\u00e9ho bodu)<\/li>\n
  7. Aplikujte K-means (k=4) na mno\u017eine bodov \u2013 koncov\u00fdch bodov detegovan\u00fdch \u010diar. V\u00fdsledn\u00e9 centroidy pre klastre vykreslite do p\u00f4vodn\u00e9ho obr\u00e1zka.<\/li>\n
  8. Aplikujte K-means (k=1) na mno\u017eine 4 centroidov. Zakreslite v\u00fdsledn\u00fd centroid \u2013 v ide\u00e1lnom pr\u00edpade by to mal by\u0165 vanishing point. Vo v\u00fdslednom obr\u00e1zku nech s\u00fa iba poz\u00edcie centroidov. Av\u0161ak vykreslite osobitne aj \u010diastkov\u00e9 rie\u0161enia vr\u00e1tane v\u00fdstupu po detekcii \u010diar.<\/li>\n<\/ol>\n

    Repozit\u00e1r je v githube pr\u00e1zdny. Vstupn\u00e9 obr\u00e1zky si h\u013ead\u00e1te samostatne.<\/p>\n

    A2: RTG detekcia zlomeniny (LINK na github classroom<\/a>)<\/h2>\n

    Z\u013eahka si pre\u010d\u00edtajte nasledovn\u00fd vedeck\u00fd pr\u00edspevok:<\/p>\n

    Basha, Cmak Zeelan, et al. \u201eEnhanced computer aided bone fracture detection employing X-ray images by Harris Corner technique.\u201c 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2020. <\/em><\/p>\n

    \u010cl\u00e1nok na stiahnutie tu: PDF<\/a> (ak by bol probl\u00e9m sa k nemu dosta\u0165, viem preposla\u0165).<\/p>\n

    Implementujte pop\u00edsan\u00fd postup:<\/p>\n