{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T09:42:46Z","timestamp":1785404566511,"version":"3.56.0"},"reference-count":30,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T00:00:00Z","timestamp":1783468800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Consejo Nacional de Ciencia y Tecnolog\u00eda (CONACYT), currently under the Secretar\u00eda de Ciencia, Humanidades, Tecnolog\u00eda e Innovaci\u00f3n","award":["786762"],"award-info":[{"award-number":["786762"]}]},{"award":["786762"],"award-info":[{"award-number":["786762"]}],"id":[{"id":"https:\/\/ror.org\/03pr08s76","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Voxel representations provide a simple way to represent three-dimensional objects as binary occupancy signals, but dense voxel grids and direct sparse encodings remain costly at medium and high resolutions. This paper addresses the gap between conventional dense-grid, octree, and point-cloud-codec representations and deterministic contour-first source serialization for exact binary voxel occupancy. We propose a contour-based chain-code serialization that decomposes a voxel grid into two-dimensional slices, extracts foreground components and holes, encodes their contours using F4, 3OT, and F8 variants, and separates contour symbols from positional metadata before applying general-purpose lossless compression. The method is evaluated on 3983 ModelNet40-derived voxelized objects across 40 classes and resolutions N = 8, 16, 32, 64, 128, 256, and 512, using the X-axis for the main evaluation. It is compared against OCC1, BINVOX, breadth-first octree masks, and geometry-only G-PCC. The proposed streams are not competitive at N = 8, where zstd-compressed octree masks achieve the best mean bpv. From N = 16 onward, however, the best proposed stream outperforms the strongest evaluated baseline, with gains increasing from 20.93% at N = 16 to 84.37% at N = 512. The best proposed configuration is zstd + 3OT at N = 8 and N = 16, while zstd + F8 dominates from N = 32 through N = 512. Entropy, ablation, timing, memory, and validation analyses further show that the advantage comes from the interaction between contour-aware source serialization and backend compression, rather than from the backend compressor alone.<\/jats:p>","DOI":"10.3390\/e28070774","type":"journal-article","created":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T14:17:51Z","timestamp":1783606671000},"page":"774","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Contour-Based Chain-Code Serialization for Lossless Compression of Voxelized 3D Objects"],"prefix":"10.3390","volume":"28","author":[{"given":"Esteban-Alejandro","family":"Dur\u00e1n-Y\u00e1\u00f1ez","sequence":"first","affiliation":[{"name":"Departamento de Sistemas y Computaci\u00f3n, Tecnol\u00f3gico Nacional de M\u00e9xico\/Instituto Tecnol\u00f3gico de Aguascalientes, Av. Adolfo L\u00f3pez Mateos #1801 Ote., Fracc. Bona Gens, Aguascalientes 20255, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mario-Alberto","family":"Rodr\u00edguez-D\u00edaz","sequence":"additional","affiliation":[{"name":"Departamento de Sistemas y Computaci\u00f3n, Tecnol\u00f3gico Nacional de M\u00e9xico\/Instituto Tecnol\u00f3gico de Aguascalientes, Av. Adolfo L\u00f3pez Mateos #1801 Ote., Fracc. Bona Gens, Aguascalientes 20255, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ricardo","family":"Mendoza-Gonz\u00e1lez","sequence":"additional","affiliation":[{"name":"Departamento de Sistemas y Computaci\u00f3n, Tecnol\u00f3gico Nacional de M\u00e9xico\/Instituto Tecnol\u00f3gico de Aguascalientes, Av. Adolfo L\u00f3pez Mateos #1801 Ote., Fracc. 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