{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:GLHA5D2BZHQ7KSMSGAUP7AHKR4","short_pith_number":"pith:GLHA5D2B","canonical_record":{"source":{"id":"1708.00227","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-01T09:52:03Z","cross_cats_sorted":[],"title_canon_sha256":"b448fdaef1fae0d6cbeae45932d248f321517ec2c1ea181ba86e5f62074c549c","abstract_canon_sha256":"c769e5e1c25aa583764e77ead971aed472baae6747b67e24a2a8fbabc03d6cb1"},"schema_version":"1.0"},"canonical_sha256":"32ce0e8f41c9e1f549923028ff80ea8f1172d48102fc83eeba606c283998a90a","source":{"kind":"arxiv","id":"1708.00227","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.00227","created_at":"2026-05-18T00:39:05Z"},{"alias_kind":"arxiv_version","alias_value":"1708.00227v1","created_at":"2026-05-18T00:39:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.00227","created_at":"2026-05-18T00:39:05Z"},{"alias_kind":"pith_short_12","alias_value":"GLHA5D2BZHQ7","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"GLHA5D2BZHQ7KSMS","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"GLHA5D2B","created_at":"2026-05-18T12:31:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:GLHA5D2BZHQ7KSMSGAUP7AHKR4","target":"record","payload":{"canonical_record":{"source":{"id":"1708.00227","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-01T09:52:03Z","cross_cats_sorted":[],"title_canon_sha256":"b448fdaef1fae0d6cbeae45932d248f321517ec2c1ea181ba86e5f62074c549c","abstract_canon_sha256":"c769e5e1c25aa583764e77ead971aed472baae6747b67e24a2a8fbabc03d6cb1"},"schema_version":"1.0"},"canonical_sha256":"32ce0e8f41c9e1f549923028ff80ea8f1172d48102fc83eeba606c283998a90a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:39:05.760987Z","signature_b64":"4PZokgVKxGixttKdZkfX4YBn4MKKYSrtLjAvyvQ4QPYiBY6+jIeVIOFlIop0e7DiNcFz4IcfQQx0/fiic1UXDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"32ce0e8f41c9e1f549923028ff80ea8f1172d48102fc83eeba606c283998a90a","last_reissued_at":"2026-05-18T00:39:05.760374Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:39:05.760374Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1708.00227","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:39:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Kg3Ib+mWdkMzFrf9I6eYTMud0KXgBHytlilbtsa21Qkfy9EHoLgqW8kxAwdxq/CrKbwefSShC1pTgFW3zGCTDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T21:00:25.505169Z"},"content_sha256":"54c87ba0bb95bef61c0969db11ce9f7e157f0e191d3e739e6f77f8e0bcaf6171","schema_version":"1.0","event_id":"sha256:54c87ba0bb95bef61c0969db11ce9f7e157f0e191d3e739e6f77f8e0bcaf6171"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:GLHA5D2BZHQ7KSMSGAUP7AHKR4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"HMM-based Indic Handwritten Word Recognition using Zone Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ayan Das, Ayan Kumar Bhunia, Partha Pratim Roy, Prasenjit Dey, Umapada Pal","submitted_at":"2017-08-01T09:52:03Z","abstract_excerpt":"This paper presents a novel approach towards Indic handwritten word recognition using zone-wise information. Because of complex nature due to compound characters, modifiers, overlapping and touching, etc., character segmentation and recognition is a tedious job in Indic scripts (e.g. Devanagari, Bangla, Gurumukhi, and other similar scripts). To avoid character segmentation in such scripts, HMM-based sequence modeling has been used earlier in holistic way. This paper proposes an efficient word recognition framework by segmenting the handwritten word images horizontally into three zones (upper, "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.00227","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:39:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2a/rqm4tMjGho5jYe98XmCuO9VDwpRpVi93TreiXcO16oWLnbGUlpZGt5BuOwhnyctFr2lXERmx/WCvyXJ02DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T21:00:25.505583Z"},"content_sha256":"75ca7a6f95b889a994c9a33d2ea4bae60f94d99ea6b66e638aeba1cf7d79686f","schema_version":"1.0","event_id":"sha256:75ca7a6f95b889a994c9a33d2ea4bae60f94d99ea6b66e638aeba1cf7d79686f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GLHA5D2BZHQ7KSMSGAUP7AHKR4/bundle.json","state_url":"https://pith.science/pith/GLHA5D2BZHQ7KSMSGAUP7AHKR4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GLHA5D2BZHQ7KSMSGAUP7AHKR4/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-25T21:00:25Z","links":{"resolver":"https://pith.science/pith/GLHA5D2BZHQ7KSMSGAUP7AHKR4","bundle":"https://pith.science/pith/GLHA5D2BZHQ7KSMSGAUP7AHKR4/bundle.json","state":"https://pith.science/pith/GLHA5D2BZHQ7KSMSGAUP7AHKR4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GLHA5D2BZHQ7KSMSGAUP7AHKR4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:GLHA5D2BZHQ7KSMSGAUP7AHKR4","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"c769e5e1c25aa583764e77ead971aed472baae6747b67e24a2a8fbabc03d6cb1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-01T09:52:03Z","title_canon_sha256":"b448fdaef1fae0d6cbeae45932d248f321517ec2c1ea181ba86e5f62074c549c"},"schema_version":"1.0","source":{"id":"1708.00227","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.00227","created_at":"2026-05-18T00:39:05Z"},{"alias_kind":"arxiv_version","alias_value":"1708.00227v1","created_at":"2026-05-18T00:39:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.00227","created_at":"2026-05-18T00:39:05Z"},{"alias_kind":"pith_short_12","alias_value":"GLHA5D2BZHQ7","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"GLHA5D2BZHQ7KSMS","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"GLHA5D2B","created_at":"2026-05-18T12:31:18Z"}],"graph_snapshots":[{"event_id":"sha256:75ca7a6f95b889a994c9a33d2ea4bae60f94d99ea6b66e638aeba1cf7d79686f","target":"graph","created_at":"2026-05-18T00:39:05Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"This paper presents a novel approach towards Indic handwritten word recognition using zone-wise information. Because of complex nature due to compound characters, modifiers, overlapping and touching, etc., character segmentation and recognition is a tedious job in Indic scripts (e.g. Devanagari, Bangla, Gurumukhi, and other similar scripts). To avoid character segmentation in such scripts, HMM-based sequence modeling has been used earlier in holistic way. This paper proposes an efficient word recognition framework by segmenting the handwritten word images horizontally into three zones (upper, ","authors_text":"Ayan Das, Ayan Kumar Bhunia, Partha Pratim Roy, Prasenjit Dey, Umapada Pal","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-01T09:52:03Z","title":"HMM-based Indic Handwritten Word Recognition using Zone Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.00227","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:54c87ba0bb95bef61c0969db11ce9f7e157f0e191d3e739e6f77f8e0bcaf6171","target":"record","created_at":"2026-05-18T00:39:05Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"c769e5e1c25aa583764e77ead971aed472baae6747b67e24a2a8fbabc03d6cb1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-01T09:52:03Z","title_canon_sha256":"b448fdaef1fae0d6cbeae45932d248f321517ec2c1ea181ba86e5f62074c549c"},"schema_version":"1.0","source":{"id":"1708.00227","kind":"arxiv","version":1}},"canonical_sha256":"32ce0e8f41c9e1f549923028ff80ea8f1172d48102fc83eeba606c283998a90a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"32ce0e8f41c9e1f549923028ff80ea8f1172d48102fc83eeba606c283998a90a","first_computed_at":"2026-05-18T00:39:05.760374Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:39:05.760374Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4PZokgVKxGixttKdZkfX4YBn4MKKYSrtLjAvyvQ4QPYiBY6+jIeVIOFlIop0e7DiNcFz4IcfQQx0/fiic1UXDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:39:05.760987Z","signed_message":"canonical_sha256_bytes"},"source_id":"1708.00227","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:54c87ba0bb95bef61c0969db11ce9f7e157f0e191d3e739e6f77f8e0bcaf6171","sha256:75ca7a6f95b889a994c9a33d2ea4bae60f94d99ea6b66e638aeba1cf7d79686f"],"state_sha256":"981b7bcb5a63c36e8fea990bed346b9328586acb2636b14658c34d75ededdd52"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Fb+2xpLR3TmUkHRYmfSHksy0GNXaM2HLGeEUoH/4HzC2CswNYBlP8C4p4S7VEKcSwA/HvLRNs6mQaxuJIqVfDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T21:00:25.508051Z","bundle_sha256":"8e3c7c10c0984aeca22921dccfc1b5389d7718522e6245013b50acd60a23717e"}}